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Introduction to Prolog Programming

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1. sse 55 compound cece eee eee ri compound Lem 5 concatenation of lists 16 O Oa E ET ES 43 CONSULE 1 2 ce eee 7 CULIONt EEN 28 Qo259919092 995999999975 99 UPS OPPSPU Of problems with 40 D debugging cece cece 57 disjunction eee eee eee 43 E CMe y MISC qe L 15 F LOC EE 5 51 Lll D cecceesebere0eec eeePLes eee TE ri TUA DOT 22229929929 2299229429999 9999 5 49 60 G goal execution 6 ovS ve Servo eure tes 9 52 SO UC VOI re EE ace arene end POM 5 H head of a Db iru ore ob d 15 bead ol a Tule voxosok E E E Se A 6 head tail pattern 2 4 16 Help cusseucneeaunecumequnequaequees 8 See ue ger us ou ood 29 999 od a 51 I THO ter Ger EE 55 infix operator serere eee 28 IS OpPETATOI quinq eu decas ui ded 2l L Ug eee ows 18 Ee GE 18 CS re l3 ERRDD eens ee ee ee ee qaaa acq adea gan 15 list notation Eeer 15 head tail pattern 16 MGCL codes ones yes odes pees ress 15 literature 2 0 eee 1 M EECH A s asasasasasesaseeas 8 21 52 Operators eee ee eee ol MEMD CR 7 ososesesevedsesesese5en ese es 18 N negation as failure Lus 42 17 Op taeda dada 99989922999 999 dada de T EE EE 5 O occurs CHECK 6 cu sia chun gene tees tied 53 OD wm 30 operator Ins 28 ELE D EE 28 Index operator definition 30 P parent goOal cc
2. 2 2 4 5 5 6 Logic Foundations of Prolog 6 1 Translation of Prolog Clauses into Formulas 6 2 Horn Formulas and Resolution 6 3 Exercises 2 2 2 52 5 2 A Recursive Programming A 1 Complete Induction a A 2 The Recursion Principle A 3 What Problems to Solve 040 AA DODUS IB a nek e ee UR xam ee m 09 e dh Index Contents Chapter 1 The Basics Prolog programming in logic is one of the most widely used programming languages in artificial intelligence research As opposed to imperative languages such as C or Java which also happens to be object oriented it is a declarative programming language That means when implementing the solution to a problem instead of specifying how to achieve a certain goal in a certain situation we specify what the situation rules and facts and the goal query are and let the Prolog interpreter derive the solution for us Prolog is very useful in some problem areas such as artificial intelligence natural language processing databases but pretty useless in others such as graphics or numerical algorithms By following this course you will learn how to use Prolog as a programming language to solve practical problems in computer science and artificial intelligence You will also learn how the Prolog interpreter actually works The latter will include an introduction to the logical foundatio
3. 1 2 Prolog Syntax This section describes the most basic features of the Prolog programming language 1 2 1 Terms The central data structure in Prolog is that of a term There are terms of four kinds atoms numbers variables and compound terms Atoms and numbers are sometimes grouped together and called atomic terms Atoms Atoms are usually strings made up of lower and uppercase letters digits and the underscore starting with a lowercase letter The following are all valid Prolog atoms elephant b abcXYZ x_123 another_pint_for_me_please On top of that also any series of arbitrary characters enclosed in single quotes denotes an atom Ulle Endriss And Introduction to Prolog Programming 5 gt This is also a Prolog atom Finally strings made up solely of special characters like lt gt amp check the manual of your Prolog system for the exact set of these characters are also atoms Examples 3 29 Numbers All Prolog implementations have an integer type a sequence of digits optionally preceded by a minus Some also support floats Check the manual for details Variables Variables are strings of letters digits and the underscore starting with a capital letter or an underscore Examples X Elephant 24711 X 1 2 MyVariable _ The last one of the above examples the single underscore constitutes a special case It is called the anonymous variable and is used when the value of
4. 3 Insert a space after every comma inside a compound term born mary yorkshire 01 01 1980 4 Write short clauses with bodies consisting of only a few goals If necessary split into shorter sub clauses 5 Choose meaningful names for your variables and atoms 1 5 Exercises Exercise 1 1 Iry to answer the following questions first by hand and then verify your answers using a Prolog interpreter a Which of the following are valid Prolog atoms f loves john mary Mary cl Hello this is it b Which of the following are valid names for Prolog variables a A Paul Hello a 123 _ abc x2 c What would a Prolog interpreter reply given the following query f a b f X Y d Would the following query succeed loves mary john loves John Mary Why e Assume a program consisting only of the fact a B B has been consulted by Prolog How will the system react to the following query T aly Ky aX Y aCY 2 alze 100 Why Exercise 1 2 Read the section on matching again and try to understand what s hap pening when you submit the following queries to Prolog a myFunctor 1 2 X X myFunctor Y Y D Ye 35 cur d em fox Xe Ve gel c writeC One X writeC Two Ulle Endriss And Introduction to Prolog Programming 13 Exercise 1 3 Draw the family tree corresponding to the following Prolog program female mary female sandra female juliet female lisa
5. List elephant dog donkey rabbit No add donkey dog donkey rabbit List List dog donkey rabbit No The important bit here is that there are no wrong alternative solutions The following Prolog program does the job add Element List List member Element List add Element List Element Listl If the element to be inserted can be found in the list already the output list should be identical with the input list As this is the only correct solution we prevent Prolog from Ulle Endriss And Introduction to Prolog Programming Al backtracking by using a cut Otherwise i e if the element is not already in the list we use the head tail pattern to construct the output list This is an example for a program where cuts can be problematic When used as specified namely with a variable in the third argument position add 3 works fine If however we put an instantiated list in the third argument Prolog s reply can be different from what you might expect Example add a La b c d la a b c dl Yes Compare this with the definition of the add 3 predicate from above and try to understand what s happening here One possible solution would be to explicitly say in the second clause that member Element List should not succeed rather than using a cut in the first clause We are going to see how to do this using negation in the next section An alternative solution would be to rewri
6. X mouse jellyfish zebra Yes Ulle Endriss And Introduction to Prolog Programming 19 2 4 Exercises Exercise 2 1 Write a Prolog predicate analyse list 1 that takes a list as its argu ment and prints out the list s head and tail on the screen If the given list is empty the predicate should put out an accordant message If the argument term isn t a list at all the predicate should just fail Examples analyse list dog cat horse cow This is the head of your list dog This is the tail of your list cat horse cow Yes analyse list This is an empty list Yes analyse list sigmund freud No Exercise 2 2 Write a Prolog predicate membership 2 that works like the built in predicate member 2 without using member 2 Hint This exercise like many others can and should be solved using a recursive approach and the head tail pattern for lists Exercise 2 3 Implement a Prolog predicate remove duplicates 2 that removes all duplicate elements from a list given in the first argument and returns the result in the second argument position Example 7 remove duplicates a b a c d d List List b a c d Yes Exercise 2 4 Write a Prolog predicate reverse list 2 that works like the built in predicate reverse 2 without using reverse 2 Example reverse list tiger lion elephant monkey List List monkey elephant lion tiger Yes Exercise 2 5 Consider the following Pro
7. Arithmetic Expressions If you ve tried to use numbers in Prolog before you might have encountered some unex pected behaviour of the system The first part of this section clarifies this phenomenon After that an overview of the arithmetic operators available in Prolog is given 3 1 The is Operator for Arithmetic Evaluation Simple arithmetic operators such as or are as you know valid Prolog atoms There fore also expressions like 3 5 are valid Prolog terms More conveniently they can also be written as infix operators like in 3 5 Without specifically telling Prolog that we are interested in the arithmetic properties of such a term these expressions are treated purely syntactically i e their values are not evaluated That means using won t work the way you might have expected Ts 3 deu m No The terms 3 5 and 8 do not match the former is a compound term whereas the latter is a number To check whether the sum of 3 and 5 is indeed 8 we first have to tell Prolog to arithmetically evaluate the term 3 5 This is done by using the built in operator is We can use it to assign the value of an arithmetic expression to a variable After that it is possible to match that variable with another number Let s rewrite our previous example accordingly fe X 189 3 L5 X 85 A 8 Yes We could check the correctness of this addition also directly by putting 8 instead of the variable on the left hand side of t
8. male peter male paul male dick male bob male harry parent bob lisa parent bob paul parent bob mary parent juliet lisa parent juliet paul parent juliet mary parent peter harry parent lisa harry parent mary dick parent mary sandra After having copied the given program define new predicates in terms of rules using male 1 female 1 and parent 2 for the following family relations a father a b sister c grandmother d cousin You may want to use the operator which is the opposite of A goal like X Y succeeds if the two terms X and Y cannot be matched Example X is the brother of Y if they have a parent Z in common and if X is male and if X and Y don t represent the same person In Prolog this can be expressed through the following rule brother X Y parent Z X parent Z Y male X X Y 14 Chapter 1 The Basics Exercise 1 4 Most people will probably find all of this rather daunting at first Read the chapter again in a few weeks time when you will have gained some programming experience in Prolog and enjoy the feeling of enlightenment The part on the syntax of the Prolog language and the stuff on matching and goal execution are particularly important Chapter 2 List Manipulation This chapter introduces a special notation for lists one of the most important data structures in Prolog and provides some examples for how to work wi
9. variable is of no particular interest Multiple occurrences of the anonymous variable in one expression are assumed to be distinct i e their values don t necessarily have to be the same More on this later Compound terms Compound terms are made up of a functor a Prolog atom and a number of arguments Prolog terms i e atoms numbers variables or other com pound terms enclosed in parentheses and separated by commas The following are some examples for compound terms is bigger horse X f g X _ 7 My Functor dog It s important not to put any blank characters between the functor and the opening parentheses or Prolog won t understand what you re trying to say In other places however spaces can be very helpful for making programs more readable The sets of compound terms and atoms together form the set of Prolog predicates A term that doesn t contain any variables is called a ground term 1 2 2 Clauses Programs and Queries In the introductory example we have already seen how Prolog programs are made up of facts and rules Facts and rules are also called clauses Facts A fact is a predicate followed by a dot Examples bigger whale _ life is beautiful The intuitive meaning of a fact is that we define a certain instance of a relation as being true 6 Chapter 1 The Basics Rules A rule consists of a head a predicate and a body a sequence of predicates separated by commas Head and body are separate
10. 2 2 3 1 5 0 5 3 1 1 10 0 X X 4 1 15 0 2 2 5 3 Yes Hints Before you even start thinking about how to do this in Prolog recall how the sum of two polynomials is actually computed A rather simple solution is possible using the built in predicate select 3 Note that the list representation of the sum of two polynomials that don t share any exponents is simply the concatenation of the two lists representing the arguments Chapter 4 Operators In the chapter on arithmetic expressions we have already seen some operators Several of the predicates associated with arithmetic operations are also predefined operators This chapter explains how to define your own operators which can then be used instead of normal predicates 4 1 Precedence and Associativity Precedence From mathematics and also from propositional logic you know that the precedence of an operator determines how an expression is supposed to be interpreted For example binds stronger than V which is why the formula PV Q R is interpreted as P V Q R and not the other way round In Prolog every operator is associated with an integer number in SWI Prolog between 0 and 1200 denoting its precedence The lower the precedence number the stronger the operator is binding The arithmetic operator for example has a precedence of 400 has a precedence of 500 This is why when evaluating the term 2 3 5 Prolog will f
11. Goal Execution s 2 22 L 9 LA A Natteror ptyl xw xem c 3e ox xoxo 9 XO we we BE X 11 1 5 Exercis s 4462642485 50654 BOROE SCR ROBORE ROS x05 4 45 cinta Ls 2 List Manipulation 15 2l JNOUGUIOIL e oe x Be wee 9 Be Roue ege mor ch o9 X 6 E Pow Ue Buc we ws 15 222 dieat 2d SEO aos eem UR RUE PS WOES eek be ees eee gw s 15 2 9 Some Built in Predicates for List Manipulation 18 2 4 JEGUGPOISOS x wuwgow m m4 4 08 99 RR ROW EGRE RU WORSE seh RR XS E 19 3 Arithmetic Expressions 21 3 1 The is Operator for Arithmetic Evaluation 21 3 2 Predefined Arithmetic Functions and Relations 22 Oo Esci wx wc m7 GERBER ES RE RE AUR OR mo P EEE EES 23 4 Operators 27 4 1 Precedence and Associativity ooo e ee 27 4 2 Declaring Operators with opn llle 30 AO Eor 4 5 6 54542 Som oA BBG Oe EE ee 88 505 9 ew Se Ux um S 3l 5 Backtracking Cuts and Negation 35 5 1 Backtracking and Cuts oaoa a 35 5 1 1 Backtracking Revisited aoaaa aa a 35 5 1 2 Problems with Backtracking 36 DLS Tntrod cing CUS ss ssd s peat R9 AE IR ede Ris Roo ar vi 5 1 4 Problems with Cuts 5 2 Negation as Failure 0008 e ee 5 2 1 The Closed World Assumption 5 2 2 The Operator 22 622 be eee ase 9 9 Disunction ee ee ee ee 0 4 Example Evaluating Logic Formulas 5 5 Exercises 2
12. doesn t make sense When generating these examples I always pressed to get all alternatives This is why at the end of each query Prolog answered with No 30 Chapter 4 Operators yfy makes no sense structuring would be impossible fy prefix associative yt oo associative xt postfix ERR Table 4 1 Associativity patterns for operators in Prolog 4 2 Declaring Operators with op 3 Now we want to define our own operators Recall the example on big and not so big animals from Chapter 1 Maybe instead of writing terms like is_bigger elephant monkey we would prefer to be able to express the same thing using is_bigger as an infix operator elephant is_bigger monkey This is possible but we first have to declare is_bigger as an operator As precedence we could choose say 300 It doesn t really matter as long as it is lower than 700 the precedence of and greater than 0 What should the associativity pattern be We already said it s going to be an infix operator As arguments we only want atoms or variables i e terms of precedence 0 Therefore we should choose xfx to prevent users from nesting is_bigger expressions Operators are declared using the op 3 predicate which has the same syntax as current_op 3 The difference is that this one actually defines the operator rather than retrieving its definition Therefore all arguments have to be instantiated Again the first argument denotes t
13. it Here s an example bigger donkey dog Yes The query bigger donkey dog i e the question Is a donkey bigger than a dog succeeds because the fact bigger donkey dog has previously been communicated to the Prolog system Now is a monkey bigger than an elephant bigger monkey elephant No No it s not We get exactly the answer we expected the corresponding query namely bigger monkey elephant fails But what happens when we ask the other way round bigger elephant monkey No According to this elephants are not bigger than monkeys This is clearly wrong as far as our real world is concerned but if you check our little program again you will find that it says nothing about the relationship between elephants and monkeys Still we know that if elephants are bigger than horses which in turn are bigger than donkeys which in turn are bigger than monkeys then elephants also have to be bigger than monkeys In mathematical terms the bigger relation is transitive But this has also not been defined in our program The correct interpretation of the negative answer Prolog has given is the following from the information communicated to the system it cannot be proved that an elephant is bigger than a monkey If however we would like to get a positive reply for a query like bigger elephant monkey we have to provide a more accurate description of the world One way of doing this would be to add the
14. marry that girl The MI5 provides the committee with a database of women of the appropriate age The entries are ordered according to the order the prince would have met them on his ride through the country Written as a list of Prolog facts it looks something like this beautiful claudia beautiful sharon beautiful denise intelligent margaret intelligent sharon After some intensive thinking the Prolog sub committee comes up with the following ingenious rule bride Girl beautiful Girl intelligent Girl Let s leave the cut in the second line unconsidered for the moment Then a query of the form bride X will succeed if there is a girl X for which both the facts beautiful X and intelligent X can be found in the database Therefore the first requirement identi fied by the psychologists will be fulfilled The variable X would then be instantiated with the girl s name In order to incorporate the second condition the Prolog experts had to add the cut If the subgoal beautiful Girl succeeds i e if a fact of the form beautiful X can be found and it will be the first such fact then that choice will be final even if the subgoal intelligent X for the same X should fail 40 Chapter 5 Backtracking Cuts and Negation Given the above database this is rather tragic for our prince The first beautiful girl he d meet would be Claudia and he d fall in love with her immediately and for ever
15. predicate to compute factorials factorial 1 1 base case factorial N Result recursion step N gt 1 Ni is N 1 factorial N1 Resulti Result is Result N Ulle Endriss And Introduction to Prolog Programming 57 Take an example say the query factorial 5 X and go through the goal execution process step by step just as Prolog would and just as you would if you wanted to compute the value of 5 systematically by yourself Another example The following predicate can be used to compute the length of a list it does the same as the built in predicate length 2 len C 0 base case len _ Tail N recursion step len Tail N1 N is N1 1 A 3 What Problems to Solve You can only use recursion if the class of problems you want to solve can somehow be parametrised Typically parameters determining the complexity of a problem are natural numbers or in Prolog lists or rather their length You have to make sure that every recursion step will really transform the problem into the next simpler case and that the base case will eventually be reached That is if your problem complexity depends on a number make sure it is striving towards the number associated with the base case In the factorial 2 example the first argument is striving towards 1 in the 1en 2 example the first argument is striving towards the empty list Understanding it The recursion principle itself is very simple and app
16. remaining facts like e g bigger elephant monkey to our program For our little example this would mean adding another 5 facts Clearly too much work and probably not too clever anyway The far better solution would be to define a new relation which we will call is_bigger as the transitive closure don t worry if you don t know what that means Ulle Endriss And Introduction to Prolog Programming 3 of bigger Animal X is bigger than animal Y either if this has been stated as a fact or if there is an animal Z for which it has been stated as a fact that animal X is bigger than animal Z and it can be shown that animal Z is bigger than animal Y In Prolog such statements are called rules and are implemented like this is_bigger X Y bigger X Y is_bigger X Y bigger X Z is_bigger Z Y In these rules means something like if and the comma between the two terms bigger X Z and is_bigger Z Y stands for and X Y and Z are variables which in Prolog is indicated by using capital letters You can think of the the bigger facts as data someone has collected by browsing through the local zoo and comparing pairs of animals The implementation of is bigger on the other hand could have been provided by knowledge engineer who may not know anything at all about animals but understands the general concept of something being bigger than something else and thereby has the ability to formulate general rules regarding
17. that set Of course we can also translate single clauses For example the query is_bigger elephant X is bigger X donkey corresponds to the following first order formula Vx is bigger elephant x is_bigger x donkey L As you know queries can also be part of a Prolog program in which case they are preceded by i e such a formula could also be part of a set corresponding to an entire program To summarise when translating a Prolog program i e a sequence of clauses into a set of logic formulas you have to carry out the following steps 1 Every Prolog predicate is mapped to an atomic first order logic formula syntactt cally both are exactly the same you can just rewrite them without making any changes Ulle Endriss And Introduction to Prolog Programming 51 2 Commas separating subgoals correspond to conjunctions in logic i e you have to replace every comma between two predicates by a in the formula 3 Prolog rules are mapped to implications where the rule body is the antecedent and the rule head the consequent i e rewrite as and change the order of head and body 4 Queries are mapped to implications where the body of the query is the antecedent and the consequent is L i e rewrite or as gt which is put after the translation of the body and followed by L 5 Each variable occurring in a clause has to be universally quantified in the formula i e write Vx in front of t
18. useful to have a more compact notation corresponding to the comma for conjunc tion In such cases you can use semicolon to separate two subgoals As an example consider the following definition of parent 2 parent X Y father X Y parent X Y mother X Y This means X can be shown to be the parent of Y if X can be shown to be the father of Y or if X can be shown to be the mother of Y The same definition can also be given more compactly parent X Y father X Y mother X Y Note that the precedence value of semicolon is higher than that of comma Therefore when implementing a disjunction inside a conjunction you have to structure your rule body using parentheses The semicolon should only be used in exceptional cases As it can easily be mixed up with the comma it makes programs less readable 5 4 Example Evaluating Logic Formulas As an example let s try to write a short Prolog program that may be used to evaluate a row in a truth table Assume appropriate operator definitions have been made before see for example the exercises at the end of the chapter on operators Using those operators we want to be able to type a Prolog term corresponding to the logic formula in question with the propositional variables being replaced by a combination of truth values into the system and get back the truth value for that row of the table In order to compute the truth table for A B we
19. In Prolog this corresponds to the subgoal beautiful Girl being successful with the variable instantiation Girl claudia And it stays like this forever because af ter having executed the cut that choice cannot be changed anymore As it happens Claudia isn t the most amazingly intelligent young person that you might wish her to be which means they cannot get married In Prolog again this means that the subgoal intelligent Girl with the variable Girl being bound to the value claudia will not succeed because there is no such fact in the program That means the entire query will fail Even though there is a name of a girl in the database who is both beautiful and intelligent Sharon the prince s quest for marriage is bound to fail bride X No 5 1 4 Problems with Cuts Cuts are very useful to guide the Prolog interpreter towards a solution But this doesn t come for free By introducing cuts we give up some of the nice declarative character of Prolog and move towards a more procedural system This can sometimes lead to unexpected results To illustrate this let s implement a predicate add 3 to insert an element into a list if that element isn t already a member of the list The element to be inserted should be given as the first argument the list as the second one The variable given in the third argument position should be matched with the result Examples add elephant dog donkey rabbit List
20. X No This means that Prolog cannot provide any example for a person X that would be single This is so because our little database of married people is all that Prolog knows about in this example Where to use We have mentioned already that the operator can be applied to any valid Prolog goal Recall what this means Goals are either sub goals of a query or subgoals of a rule body Facts and rule heads aren t goals Hence it is not possible to negate a fact or the head of a rule This perfectly coincides with what has been said about the closed world assumption and the notion of negation as failure it is not possible to explicitly declare a predicate as being false 5 3 Disjunction The comma in between two subgoals of a query or a rule body denotes a conjunction The entire goal succeeds if both the first and the second subgoal succeed We already know one way of expressing a disjunction If there are two rules with the same head in a program then this represents a disjunction because during the goal execution process Prolog could chose either one of the two rule bodies when the current goal matches the common rule head Of course it will always try the first such rule first and only execute the second one if there has been a failure or if the user has asked for alternative solutions 44 Chapter 5 Backtracking Cuts and Negation In most cases this form of disjunction is the one that should be used but sometimes it can be
21. Z KF KF KF KF X 3 Yes Call Call Call Call Exit Exit Exit Exit len dog fish tiger X TN FN ew FN FN FN FN 8 9 10 11 11 10 9 8 len dog fish tiger _G397 leap len fish tiger _L170 leap len tiger _L183 leap len _L196 leap len 0 leap len tiger 1 leap len fish tiger 2 leap len dog fish tiger 3 leap Index Symbols SEENEN 6 ee ee eee 13 Operator 2 cece eee eee eee 42 A anonymous variable 5 See EE 18 arithmetic evaluation 21 ASSOC VIL ooo ben nO E ewes 28 associativity patterns 28 29 E EE 4 49 APO E T B backtracking EE 10 35 problems 3SvIUDIE er eas 36 Dar Iob e a uda EIE 15 DOO OD ep be e e ee Eege 6 built in predicate a 6 e ee 13 NE Mi 42 append 3 cee eee eee 18 CN gu ri H RE 45 Compound l 000s fi consult 1 esses T Cur Ment EENS 28 EOL d gen 9 AS RG RS a oT di age oss Hews eas awn woes oe 8 d ee 21 lS E eee ee ea eee ee eee es 18 lengpth 2 ee ee eee ee ee ee 18 member sees 18 59 DI rmm 7 OU eeh whee hack whan riede 30 DOUSPSE D asi nee ees 18 SH EE EE 18 Sod EE 58 DIU ee sane e Ee e ee 7 WETUC ee 7 C CUN A 45 L tores mE ELETE TAEAE ETETE 5 closed world assumption 41 CONI EE 11 compilation 0 0 eee ee 1 31 complete induction
22. a clause for every variable X appearing in the clause we have to put Vz in front of the resulting formula The universal quantification implicitly inherent in Prolog programs has to be made explicit when writing logic formulas Before summarising the translation process more formally we give an example Con sider the following little program consisting of two facts and two rules bigger elephant horse bigger horse donkey is_bigger X Y bigger X Y is_bigger X Y bigger X Z is_bigger Z Y Translating this into a set of first order logic formulas yields bigger elephant horse bigger horse donkey Va Vy bigger x y 1s_bigger x y Va Vy Vz bigger x z is bigger z y is_bigger x y Note how the head of a rule is rewritten as the consequent of an implication Also note that each clause has to be quantified independently This corresponds to the fact that variables from distinct clauses are independent from each other even if they ve been given the same name For example the X in the first rule has nothing to do with the X in the second one In fact we could rename X to say Claudia throughout the first but not the second rule this would not affect the behaviour of the program In logic this is known as the renaming of bound variables If several clauses form a program that program corresponds to a set of formulas and each of the clauses corresponds to exactly one of the formulas in
23. allow it to succeed Prolog had to instantiate the variable X with the value horse If this makes us 4 Chapter 1 The Basics happy already we can press Return now and that s it In case we want to find out if there are more animals that are bigger than the donkey we can press the semicolon key which will cause Prolog to search for alternative solutions to our query If we do this once we get the next solution X elephant elephants are also bigger than donkeys Pressing semicolon again will return a No because there are no more solutions is bigger X donkey X horse X No elephant There are many more ways of querying the Prolog system about the contents of its database As a final example we ask whether there is an animal X that is both smaller than a donkey and bigger than a monkey 7 is bigger donkey X is bigger X monkey No The correct answer is No Even though the two single queries is bigger donkey X and is bigger X monkey would both succeed when submitted on their own their conjunction represented by the comma does not This section has been intended to give you a first impression of Prolog programming The next section provides a more systematic overview of the basic syntax There are a number of Prolog interpreters around How to start a Prolog session may slightly differ from one system to the other but it should not be difficult to find out by consulting the user manual of your system
24. an socrates 5 Prolog executes the new goal by again trying to match it with a rule head or a fact Obviously the goal man socrates matches the fact man socrates because they are identical This means the current goal succeeds 6 This again means that also the initial goal succeeds 1 4 A Matter of Style One of the major advantages of Prolog is that it allows for writing very short and compact programs solving not only comparatively difficult problems but also being readable and again comparatively easy to understand Of course this can only work if the programmer you pays some attention to his or her programming style As with every programming language comments do help In Prolog comments are enclosed between the two signs and like this This is a comment Comments that only run over a single line can also be started with the percentage sign Lhis is usually used within a clause aunt X Z sister X Y A comment on this subgoal parent Y Z Besides the use of comments a good layout can improve the readability of your programs significantly The following are some basic rules most people seem to agree on 1 Separate clauses by one or more blank lines 2 Write only one predicate per line and use indentation blond X father Father X blond Father mother Mother X blond Mother 12 Chapter 1 The Basics Very short clauses may also be written in a single line
25. c Y 2 Yes Another example for matching f a g X Y f X 2 Z gW hQO A e a Y h a Z g a h a W a Yes So far so good But what happens if matching is possible even though no specific variable instantiation has to be enforced like in all previous examples Consider the following query X my functor Y X my functor G177 Y G177 Yes In this example matching succeeds because X could be a compound term with the functor my functor and a non specified single argument Y could be any valid Prolog term but it has to be the same term as the argument inside X In Prolog s output this is denoted through the use of the variable G177 This variable has been generated by Prolog during execution time Its particular name _G177 in this case may be different every time the query is submitted 1 3 2 Goal Execution Submitting a query means asking Prolog to try to prove that the statement s implied by the query can be made true provided the right variable instantiations are made The search for such a proof is usually referred to as goal execution Each predicate in the query constitutes a sub goal which Prolog tries to satisfy one after the other If variables are shared between several subgoals their instantiations have to be the same throughout the entire expression If a goal matches with the head of a rule the respective variable instantiations are made inside the rule s body which the
26. call B implies _ How does that work Suppose A is false Then the first rule will fail Prolog will jump to the second one and succeed whatever B may be This is exactly what we want an implication evaluates to true whenever its antecedent evaluates to false In case cal1 A succeeds the cut in the first rule will be passed and the overall goal will succeed if and only if ca11 B does Again this is precisely what we want in classical logic 46 Chapter 5 Backtracking Cuts and Negation Remark We know that in classical logic A is equivalent to A _L Similarly instead of using in Prolog we could define our own negation operator as follows neg A call A fail neg _ 5 5 Exercises Exercise 5 1 Type the following queries into a Prolog interpreter and explain what happens a Result a Result b Result b b member X Ia b c X b Exercise 5 2 Consider the following Prolog program result E L E M result L M result a After having consulted this program what would Prolog reply when presented with the following query Try answering this question first without actually typing the program in but verify your solution later using the Prolog system result a b c d e f g X b Briefly describe what the program does and how it does what it does when the first argument of the result 2 predicate is instantiated with a list a
27. d 7 7 arithmetically equal are available The differentiation of and is crucial The former compares two evaluated arithmetic expressions whereas the later performs logical pattern matching T Q2 Aere 3 5 Yes T 24k 3 8 b No Note that unlike is arithmetic equality also works if one of its arguments evaluates to an integer and the other one to the corresponding float 3 9 Exercises Exercise 3 1 Write Prolog predicate distance 3 to calculate the distance between two points in the 2 dimensional plane Points are given as pairs of coordinates Examples distance 0 0 3 4 X X25 Yes distance 2 5 1 3 5 4 X X 7 81025 Yes Exercise 3 2 Write a Prolog program to print out a square of n x n given characters on the screen Call your predicate square 2 The first argument should be a positive integer the second argument the character any Prolog term to be printed Example square 5 ok Ox X X X X X X X X X Yes 24 Chapter 3 Arithmetic Expressions Exercise 3 3 Write a Prolog predicate fibonacci 2 to compute the nth Fibonacci number The Fibonacci sequence is defined as follows dier d Pi ee 2 Pa Frai tFn torn gt 2 Examples fibonacci 1 X A 1 Yes fibonacci 2 X X 2 Yes fibonacci 5 X X 8 Yes Exercise 3 4 Write a Prolog predicate element_at 3 that given a list and a natural
28. d by the sign and like every Prolog expression a rule has to be terminated by a dot Examples is_smaller X Y is_bigger Y X aunt Aunt Child sister Aunt Parent parent Parent Child The intuitive meaning of a rule is that the goal expressed by its head is true if we or rather the Prolog system can show that all of the expressions subgoals in the rule s body are true Programs A Prolog program is a sequence of clauses Queries After compilation a Prolog program is run by submitting queries to the in terpreter A query has the same structure as the body of a rule i e it is a sequence of predicates separated by commas and terminated by a dot They can be entered at the Prolog prompt which in most implementations looks something like this When writing about queries we often include the Examples is bigger elephant donkey 7 small X green X slimy X Intuitively when submitting a query like the last example we ask Prolog whether all its predicates are provably true or in other words whether there is an X such that smal1 X green X and slimy X are all true 1 2 3 Some Built in Predicates What we have seen so far is already enough to write simple programs by defining pred icates in terms of facts and rules but Prolog also provides a range of useful built in predicates Some of them will be introduced in this section all of them should be ex plained in the user manual of your P
29. e directly into a program file which will cause it to be executed whenever you consult that file The syntax for such queries is similar to rules but without a head Say for instance your program contains the following line write Hello have a beautiful day Then every time you consult the file this will cause the goal after to be executed consult my file pl Hello have a beautiful day my file pl compiled 0 00 sec 224 bytes Yes You can do exactly the same with operator definitions i e you could add the definition for is_bigger op 300 xfx is bigger at the beginning of the big animals program file and the operator will be available directly after compilation 4 3 Exercises Exercise 4 1 Consider the following operator definitions op 100 yfx plink op 200 xfy plonk a Have another look at Section 4 1 to find out what this actually means b Copy the operator definitions into a program file and compile it Then run the following queries and explain what is happening i tiger plink dog plink fish X plink Y 32 Chapter 4 Operators ii cow plonk elephant plink bird X plink Y iii X lion plink tiger plonk horse plink donkey c Write a Prolog predicate pp_analyse 1 to analyse plink plonk expressions The output should tell you what the principal operator is and which are the two main sub terms If the main operator is neither plink nor pl
30. e first subgoal b1 Once the right rule has been found the current subgoal is replaced with the rule body in this case al a2 The new goal to execute therefore is a1 a2 b2 In Prolog this process is repeated until there are no more subgoals left in the query In resolution this corresponds to deriving an empty disjunction in other words l1 When using variables in Prolog we have to move from propositional to first order logic The resolution rule for first order logic is basically the same as the one for propo sitional logic The difference is that it is not enough anymore just to look for com plementary literals B4 and 4B in the previous example that can be found in the set of Horn formulas but now we also have to consider pairs of literals that can be made complementary by means of unification Unification in logic corresponds to matching in Prolog The variable instantiations put out by Prolog for successful queries correspond to the unifications made during a resolution proof This short presentation has only touched the very surface of what is commonly re ferred to as the theory of logic programming The real thing goes much deeper and Ulle Endriss And Introduction to Prolog Programming 53 has been the object of intensive research for many years all over the world More details can be found in books on automated theorem proving in particular resolution more theoretically oriented books on logic programming in
31. e its value will be printed out Execution of the predicate n1 0 causes the system to skip a line Here are two examples write Hello World nl Hello World Yes X elephant write X nl elephant X elephant Yes In the second example first the variable X is bound to the atom elephant and then the value of X i e elephant is written on the screen using the write 1 predicate After skipping to a new line Prolog reports the variable binding s i e X elephant Checking the type of a Prolog term There are a number of built in predicates available that can be used to check the type of a given Prolog term Here are some examples atom elephant Yes atom Elephant No The 1 is used to indicate that this predicate takes one argument 8 Chapter 1 The Basics X f mouse compound X X f mouse Yes The last query succeeds because the variable X is bound to the compound term f mouse at the time the subgoal compound X is being executed Help Most Prolog systems also provide a help function in the shape of predicate usually called help 1 Applied to a term like the name of a built in predicate the system will display a short description if available Example help atom atom Term Succeeds if Term is bound to an atom 1 3 Answering Queries We have mentioned the issue of term matching before in these notes This concept is crucial to the way Prolog replies to querie
32. ed the Socrates example Then sit back and appreciate what you have learned Appendix A Recursive Programming Recursion has been mentioned over and over again in these notes It is not just a Prolog phenomenon but one of the most basic and most important concepts in computer science and mathematics in general Some people tend to find the idea of recursive programming difficult to grasp at first If that s you maybe you ll find the following helpful A 1 Complete Induction The concept of recursion closely corresponds to the induction principle used in mathe matics To show a statement for all natural numbers show it for a base case e g n 1 and show that from the statement being true for a particular n it can be concluded that the statement also holds for n 1 This proves the statement for all natural numbers n Let s look at an example You might recall the formula for calculating the sum of the first n natural numbers Before one can use such a formula it has to be shown that it is indeed correct 1 Claim Da induction hypothesis i 1 Proof by complete induction 1 1 1 F 1 1 d 1 pou n gt i d base case Al n 1 n nent Si Si n 1 induction step using the hypothesis i 1 i l n n 1 n 1 n 2 Lon wun CADO Y 2 2 55 56 Appendix A Recursive Programming A 2 The Recursion Principle The basic idea of recursive programming the recursion principle is the following To so
33. eee cee eee 38 postfix operator lesse 28 precedence 0 cee eee cee eens 27 predicate 0 0 ccc ec ee 5 49 prefix operator 0 e ee eee 28 DIOS Ait ee e 6 UE cocos obs ios SE VIUA T re ee 6 51 R recursive programming 56 resolution 6 cece ees 52 i e P ML 18 IB S 6 51 S EE EEN 18 oh 58 T tal OF D a E OF 15 ieee eee eee ee eee TOT 4 49 CompOund eee eee eee eee 5 EE 5 transitive close 2 translation 0 ccc ee ee eee 49 EE EE Ee 7 U UIC AO Usa v ovo rta E E E TE 52 V ENEE 5 49 PIDE MOMS tas seme Pace Versu see yas 5 W nnan he T EE EEE EE EEEE 7
34. ement Here s a very simple recursive definition of the predicate permutation 2 permutation permutation List Element Permutation 30 36 Chapter 5 Backtracking Cuts and Negation select Element List Rest permutation Rest Permutation The simplest case is that of an empty list There s just one possible permutation the empty list itself If the input list has got elements then the subgoal select Element List Rest will succeed and bind the variable Element to an element of the input list It makes that element the head of the output list and recursively calls permutation 2 again with the rest of the input list The first answer to a query will simply reproduce the input list because Element will always be assigned to the value of the head of List If further alternatives are requested however backtracking into the select subgoal takes place i e each time Element is instantiated with another element of List This will generate all possible orders of selecting elements from the input list in other words this will generate all permutations of the input list Example permutation 1 2 3 X X 1 2 3 X 1 3 2 X 2 1 3 3 Ps ll 25 oa 3l s X 3 1 2 X 3 2 1 No We have also seen other examples for exploiting the backtracking feature before like e g in Section 2 2 There we used backtracking into concat_lists 3 which is the same as the bui
35. ements before the bar If there is exactly one element before the bar it is the head and the term after the bar is the list s tail In the next example 1 is the head of the list and 2 3 4 5 is the tail which has been computed by Prolog simply by matching the list of numbers with the head tail pattern 1 2 3 4 5 Head Tail Head 1 Tail 2 3 4 5 Yes Note that Head and Tail are just names for variables We could have used X and Y or whatever instead with the same result Note also that the tail of a list more generally speaking the thing after is always a list itself Possibly the empty list but definitely a list The head however is an element of a list It could be a list as well but not necessarily as you can see from the previous example 1 is not a list The same applies to all other elements listed before the bar in a list This notation also allows us to retrieve the say second element of a given list In the following example we use the anonymous variable for the head and also for the list after the bar because we are only interested in the second element quod licet jovi non licet bovi _ X _ X licet Yes The head tail pattern can be used to implement predicates over lists in a very compact and elegant way We exemplify this by presenting an implementation of a predicate that can be used to concatenate two lists We call it concat_lists 3 When called with t
36. erence manual Functions Addition or multiplication are examples for arithmetic functions In Prolog all these functions are written in the natural way The following term shows some examples 2 3 2 X max 17 X 2 5 The max 2 expression evaluates to the largest of its two arguments and 2 5 stands for 2 to the 5th power 2 Other functions available include min 2 minimum abs 1 i absolute value sqrt 1 square root and sin 1 sinus The operator is used for integer division To obtain the remainder of an integer division modulo use the mod operator Precedence of operators is the same as you know it from mathematics i e 2 x 3 4 is equivalent to 2 3 4 etc You can use round 1 to round a float number to the next integer and float 1 to convert integers to floats All these functions can be used on the right hand side of the is operator Like max 2 these are all written as functions not as operators Ulle Endriss And Introduction to Prolog Programming 23 Relations Arithmetic relations are used to compare two evaluated arithmetic expres sions The goal X gt Y for example will succeed if expression X evaluates to a greater number than expression Y Note that the is operator is not needed here The arguments are evaluated whenever an arithmetic relation is used Besides gt the operators lower lt lower or equal gt greater or equal non equal an
37. g we usually don t make this sort of assumption Just because the duckbill might not appear in even a very big book on animals we cannot infer that it isn t an animal In Prolog on the other hand when we have a list of facts like animal elephant animal tiger animal lion and animal duckbill does not appear in that list and there are no rules with animal 1 in the head then Prolog would react to a query asking whether the duckbill was an animal as follows animal duckbill No The closed world assumption might seem a little narrow minded at first sight but you will appreciate that it is the only admissible interpretation of a Prolog reply as Prolog clauses only give sufficient not necessary conditions for a predicate to hold Note however that if you have completely specified a certain problem i e when you can be sure that for every case where there is a positive solution Prolog has all the data to be able to construct the respective proof then the notions of not provable and false coincide A No then really does mean no 5 2 2 The Operator Sometimes we might not want to ask whether a certain goal succeeds but whether it fails That is we want to be able to negate goals In Prolog this is possible using the operator This is a prefix operator that can be applied to any valid Prolog goal A goal of the form Goal succeeds if the goal Goal fails and vice versa In other words Goal succeeds if P
38. general and Prolog in particular and various scientific journals on logic programming and alike 6 3 Exercises Exercise 6 1 Translate the following Prolog program into a set of first order logic formulas parent peter sharon parent peter lucy male peter female lucy female sharon father X Y parent X Y male X Sister X Y parent Z X parent Z Y female X Exercise 6 2 Type the following query into Prolog and try to explain what happens X f X Hint This example shows that matching Prolog and unification logic are in fact not exactly the same concept Take your favourite Prolog book and read about the occurs check to find out more about this Exercise 6 3 As we have seen in this chapter the goal execution process in Prolog can be explained in terms of the resolution method By the way this also means that a Prolog interpreter could be based on a resolution based automated theorem prover implemented in a low level language such as Java or C Recall the mortal Socrates example from the introductory chapter page 10 and what has been said there about Prolog s way of deriving a solution to a query Translate that program and the query into first order logic and see if you can construct the corresponding resolution proof Compare this with what we have said about the Prolog goal execution 54 Chapter 6 Logic Foundations of Prolog process when we first introduc
39. he first two elements being instantiated to lists the third argument should be matched with the concatenation of those two lists in other words we would like to get the following behaviour concat lists 1 2 3 d e f gl X X 1 2 9 d e f g Yes The general approach to such a problem is a recursive one We start with a base case and then write a clause to reduce a complex problem to a simpler one until the base case is reached For our particular problem a suitable base case would be when one of the two input lists for example the first one is the empty list In that case the result the third argument is simply identical with the second list This can be expressed through the following fact Note that most Prolog systems already provide such a predicate usually called append 3 see Sec tion 2 3 So you do not actually have to implement this yourself Ulle Endriss And Introduction to Prolog Programming 17 concat_lists List List In all other cases i e in all cases where a query with concat_lists as the main functor doesn t match with this fact the first list has at least one element Hence it can be written as a head tail pattern Elem Listi If the second list is associated with the variable List2 then we know that the head of the result should be Elem and the tail should be the concatenation of List1 and List2 Note how this simplifies our initial problem We take away the head of the first l
40. he is operator 8 is 3 b Yes 21 22 Chapter 3 Arithmetic Expressions But note that it doesn t work the other way round 7 3 5 is 8 No This is because is only causes the argument to its right to be evaluated and then tries to match the result with the left hand argument The arithmetic evaluation of 8 yields again 8 which doesn t match the non evaluated Prolog term 3 5 To summarise the is operator is defined as follows It takes two arguments of which the second has to be a valid arithmetic expression with all variables instantiated The first argument has to be either a number or a variable representing a number A call succeeds if the result of the arithmetic evaluation of the second argument matches with the first one or in case of the first one being a number if they are identical Note that in SWI Prolog the result of the arithmetic calculation will be an integer whenever possible That means for example that the goal 1 0 is 0 5 0 5 would not succeed because 0 5 0 5 evaluates to the integer 1 not the float 1 0 In general it is better to use the operator which will be introduced in Section 3 2 instead whenever the left argument has been instantiated to a number already 3 2 Predefined Arithmetic Functions and Relations The arithmetic operators available in Prolog can be divided into functions and relations Some of them are presented here for an extensive list consult your Prolog ref
41. he operator s definition The operator is actually defined as an infix operator for which the right hand argument has to be a term of strictly lower precedence than 500 the precedence of itself whereas the left hand argument only needs to be of lower or equal precedence Given this rule it is indeed impossible to interpret 10 5 2as 10 5 2 because the precedence of the right hand argument of the principal operator is 500 i e it is not strictly lower than 500 We also say the operator associates to the left or is left associative In Prolog associativity together with such restrictions on arguments precedences is represented by atoms like yfx Here f indicates the position of the operator i e yf x denotes an infix operator and x and y indicate the positions of the arguments A y should be read as on this position a term with a precedence lower or equal to that of the operator has to occur whereas x means that on this position a term with a precedence strictly lower to that of the operator has to occur Checking precedence and associativity It is possible to check both precedence and associativity of any previously defined operator by using the predicate current_op 3 If the last of its arguments is instantiated with the name of an operator it will match the first one with the operator s precedence and the second with its associativity pattern The following example for mu
42. he precedence the second one the associativity type and the third one the name of the operator Any Prolog atom could become the name of an operator unless it is one already Our is_bigger operator is declared by submitting the following query op 300 xfx is bigger Yes Now Prolog knows it s an operator but doesn t necessarily have a clue how to evaluate the truth of an expression containing this operator This has to be programmed in terms of facts and rules in the usual way When implementing them you have the choice of either using the operator notation or normal predicate notation That means we can use the program from Chapter 1 in its present form The operator is bigger will be associated with the functor is bigger that has been used there i e after having compiled the program file we can ask queries like the following Ulle Endriss And Introduction to Prolog Programming 31 elephant is bigger donkey Yes As far as matching is concerned predicate and operator notation are considered to be identical as you can see from Prolog s reply to this query elephant is bigger tiger is bigger elephant tiger Yes Query execution at compilation time Obviously it wouldn t be very practical to redefine all your operators every time you re start the Prolog interpreter Fortunately it is possible to tell Prolog to make the definitions at compilation time More generally speaking you may put any query you lik
43. he whole formula for each variable X 6 2 Horn Formulas and Resolution The formulas we get when translating Prolog rules all have a similar structure they are implications with an atom in the consequent and a conjunction of atoms in the antecedent this implication again is usually in the scope of a sequence of universal quantifiers Abstracting from the quantification for the moment these formulas all have the following structure AALALA AAA D Such a formula can be rewritten as follows Aj Ag A A An SB a Ay A Ag An V B Va V V2A VB Note that if B is L which is the case when we translate queries we obtain the following 3A VaAg V V2A VL aA VaV V AA Hence every formula we get when translating a Prolog program into first order formulas can be transformed into a universally quantified disjunction of literals with at most one positive literal Such formulas are called Horn formulas Sometimes the term Horn formula is also used to refer to conjunctions of disjunctions of literals with at most one positive literal each that would corresponds to an entire Prolog program As A L is logically equivalent to A by translating queries as implications with L in the consequent we are basically putting the negation of the goal in a query into the set of formulas Answering a query in Prolog means showing that the set corresponding to the associated program together with the translation of that query is logically
44. his process is known as backtracking We shall exemplify the process of goal execution by means of the following famous argument All men are mortal Socrates is a man Hence Socrates is mortal In Prolog terms the first statement represents a rule X is mortal if X is a man for all X The second one constitutes a fact Socrates is a man This can be implemented in Prolog as follows mortal X man X man socrates Note that X is a variable whereas socrates is an atom The conclusion of the argument Socrates is mortal can be expressed through the predicate mortal socrates After having consulted the above program we can submit this predicate to Prolog as a query which will cause the following reaction mortal socrates Yes Prolog agrees with our own logical reasoning Which is nice But how did it come to its conclusion Let s follow the goal execution step by step 1 The query mortal socrates is made the initial goal Ulle Endriss And Introduction to Prolog Programming 11 2 Scanning through the clauses of our program Prolog tries to match mortal socrates with the first possible fact or head of rule It finds mortal X the head of the first and only rule When matching the two terms the instantia tion X socrates needs to be made 3 The variable instantiation is extended to the body of the rule i e nan X becomes man socrates 4 The newly instantiated body becomes our new goal m
45. hould allow for double negation without parentheses see examples Hint You can easily test whether your operator declarations work as intended Recall that Prolog omits all redundant parentheses when it prints out the answer to a query That means when you ask Prolog to match a variable with a formula whose structure you have indicated using parentheses those that are redundant should all disappear in the output Parentheses that are necessary however will be shown Examples Formula a implies b and c and d Formula a implies b and c and d Yes AnotherFormula neg neg a or b AnotherFormula neg neg a or b Yes ThirdFormula a or b and c ThirdFormula a or b and c Yes Exercise 4 4 Write Prolog predicate cnf 1 to test whether a given formula is in conjunctive normal form using the operators you defined for the previous exercise Examples cnf a or neg b and b or c and neg d or neg e Yes cnf a or neg b Yes cnf a and b and c or d No cnf a and b and c or dii Yes 34 Chapter 4 Operators cnf a Yes cnf neg neg a No Hint Propositional atoms correspond to atoms in Prolog You can test whether a given term is a valid Prolog atom by using the built in predicate atom 1 Chapter 5 Backtracking Cuts and Negation In this chapter you will learn a bit more on how Prolog resolves queries We will also introduce a control mechanism cu
46. ill be discarded During backtracking however also all other branches of the search tree will be visited Even if the first rule would match sometimes the second one will be picked instead and the duplicate head will remain in the list The semantically wrong output can be seen in the following example remove duplicates a b b c al List List b c al List b b c a List sS b c al 4 List as bD b 6 al s No To solve this problem we need a way of telling Prolog that even when the user or another predicate calling remove_duplicates 2 requests further solutions there are no such alternatives and the goal should fail 5 1 3 Introducing Cuts Prolog indeed provides a solution to the sort of problems discussed above It is possible to explicitly cut out backtracking choicepoints thereby guiding the proof search and prohibiting unwanted alternative solutions to a query A cut is written as It is a predefined Prolog predicate and can be placed anywhere inside a rule s body or similarly be part of a sequence of subgoals in a query Executing 38 Chapter 5 Backtracking Cuts and Negation the subgoal will always succeed but afterwards backtracking into subgoals placed before the cut inside the same rule body is not possible anymore We will define this more precisely a bit later Let s first look at our example about removing duplicate elements from a list again We change the previo
47. inconsistent A Prolog fact is simply translated into an atomic formula i e a positive literal Therefore formulas representing facts are also Horn formulas 52 Chapter 6 Logic Foundations of Prolog This is equivalent to showing that the goal logically follows from the set representing the program P AoL EK L iff PHA In plain English to show that A follows from P show that adding the negation of A to P will lead to a contradiction In principle such a proof could be accomplished using any formal proof system but usually the resolution method is chosen which is particularly suited for Horn formulas We are not going to present the resolution method in its entirety here but the basic idea is very simple This proof system has just one rule which is exemplified in the following argument all formulas involved need to be Horn formulas 3A V aA V B1 B V 3B 3A V 5A V ABs If we know A V 545 V By and B V B5 then we also know A V A5 V B because in case B is false A V 4 has to hold and in case B4 is true 5B has to hold In the example the first formula corresponds to this Prolog rule bi al a2 The second formula corresponds to a query bi b2 The result of applying the resolution rule then corresponds to the following new query al a2 b2 And this is exactly what we would have expected When executing the goal b1 b2 Prolog starts with looking for a fact or a rule head matching th
48. irst compute the product of 3 and 5 and then add it to 2 The precedence of a term is defined as 0 unless its principal functor is an operator in which case the precedence is the precedence of this operator Examples e The precedence of 3 5 is 500 The precedence of 3 3 5 5 is also 500 The precedence of sqrt 3 5 is 0 The precedence of elephant is 0 The precedence of 3 5 is 0 The precedence of 3 5 6 is 400 27 28 Chapter 4 Operators Associativity Another important concept with respect to operators is their associa tivity You probably know that there are infix operators like prefix operators like and sometimes even postfix operators like the factorial operator in mathematics In Prolog the associativity of an operator is also part of its definition But giving precedence and indicating whether it s supposed to be infix prefix or postfix is not enough to fully specify an operator Take the example of subtraction This is an infix operator and in SWI Prolog it is defined with precedence 500 Is this really all we need to know to understand Prolog s behaviour when answering the following query e ls SLO eo ee Why didn t it compute 5 2 3 and then 10 3 7 and return X 7 asthe result Well it obviously did the right thing by first evaluating the left difference 10 5 before finally subtracting 2 But this must also be part of t
49. ist and try to concatenate it with the unchanged second list If we repeat this process recursively we will eventually end up with an empty first list which is exactly the base case that can be handled by the previously implemented fact Turning this simplification algorithm into a Prolog rule is straightforward concat lists Elem Listi List2 Elem List3 concat lists Listi List2 List3 And that s it The concat_lists 3 can now be used for concatenating two given lists as specified But it is actually much more flexible than that If we call it with variables in the first two arguments and instantiate the third one with a list concat_lists 3 can be used to decompose that list If you use the semicolon key to get all alternative solutions to your query Prolog will print out all possibilities how the given list could be obtained from concatenating two lists concat lists X Y La b c dl X Y Lax bg di X a YS Ib X a b Y c d X opas s 6 Y d 3 X a b d Y No Recall that the No at the end means that there are no further alternative solutions 18 Chapter 2 List Manipulation 2 3 Some Built in Predicates for List Manipulation Prolog comes with a range of predefined predicates for manipulating lists Some of the most important ones are presented here Note that they could all easily be implemented by exploiting the head tail pattern length 2 The seco
50. licable to many problems Despite the simplicity of the principle the actual execution tree of a recursive program might become rather complicated Make an effort to really understand at least one recursive predicate definition like e g concat lists 3 see Section 2 2 or 1en 2 completely Draw the Prolog goal execution tree and do whatever else it takes After you got to the stage where you are theoretically capable of understanding a particular problem in its entirety it is usually enough to look at things more abstractly I know I defined the right base case and I know I defined a proper recursion rule which is calling the same predicate again with a simplified argument Hence it will work This is so because I understand the recursion principle I believe in it and I am able to apply it Now and forever A 4 Debugging In SWI Prolog and most other Prolog systems it is possible to debug your Prolog programs This might help you to understand better how queries are resolved it might 58 Appendix A Recursive Programming however just be really confusing This is a matter of taste Use spy 1 to put a spypoint on a predicate typed into the interpreter as a query after compilation Example spy len Spy point on len 2 Yes debug For more information on how to use the Prolog debugger check your reference manual Here s an example for the len 2 predicate defined before debug eS A SS S
51. log program whoami 20 Chapter 2 List Manipulation whoami _ _ Rest whoami Rest Under what circumstances will a goal of the form whoami X succeed Exercise 2 6 The objective of this exercise is to implement a predicate for returning the last element of a list in two different ways a Write a predicate last1 2 that works like the built in predicate last 2 using a recursion and the head tail pattern of lists b Define a similar predicate 1ast2 2 solely in terms of append 3 without using a recursion Exercise 2 7 Write a predicate replace 4 to replace all occurrences of a given ele ment second argument by another given element third argument in a given list first argument Example gt peplace ll 2 4 3 4 35 5 6y Sly 3 X List List 1 2 x 4 x 5 6 x Yes Exercise 2 8 Prolog lists without duplicates can be interpreted as sets Write a program that given such a list computes the corresponding power set Recall that the power set of a set S is the set of all subsets of S This includes the empty set as well as the set S itself Define predicate power 2 such that if the first argument is instantiated with a list the corresponding power set i e a list of lists is returned in the second position Example power a b c P P a b cl La b la cl La Lb c b Lc J Yes Note The order of the sub lists in your result doesn t matter Chapter 3
52. lt in predicate append 3 to find all possible decompositions of a given list 5 1 2 Problems with Backtracking There are cases however were backtracking is not desirable Consider for example the following definition of the predicate remove_duplicates 2 to remove duplicate elements from a given list remove duplicates remove duplicates Head Taill Result member Head Tail Ulle Endriss And Introduction to Prolog Programming 37 remove_duplicates Tail Result remove_duplicates Head Tail Head Result remove_duplicates Tail Result The declarative meaning of this predicate definition is the following Removing duplicates from the empty list yields again the empty list There s certainly nothing wrong with that The second clause says that if the head of the input list can be found in its tail the result can be obtained by recursively applying remove_duplicates 2 to the list s tail discarding the head Otherwise we get the tail of the result also by applying the predicate to the tail of the input but this time we keep the head This works almost fine The first solution found by Prolog will indeed always be the intended result But when requesting alternative solution things will start going wrong The two rules provide a choicepoint For the first branch of the search tree Prolog will always pick the first rules if that is possible i e whenever the head is a member of the tail it w
53. ltiplication shows that has precedence 400 and the same associativity pattern as subtraction current op Precedence Associativity Precedence 400 Associativity yfx Yes Ulle Endriss And Introduction to Prolog Programming 29 Here are some more examples Note that is defined twice once as subtraction infix and once as negative sign prefix current op Precedence Associativity Precedence 200 Associativity xfx No current op Precedence Associativity Precedence 500 Associativity yfx Precedence 500 Associativity fx No current op Precedence Associativity lt Precedence 700 Associativity xfx No VY e current op Precedence Associativity Precedence 700 Associativity xfx No current op Precedence Associativity Precedence 1200 Associativity xfx Precedence 1200 Associativity fx No As you can see there aren t just arithmetic operators but also stuff like and even are declared as operators From the very last example you can see that can also be prefix operator You will see an example for this in the next section Table 4 1 provides an overview of possible associativity patterns Note that it is not possible to nest non associative operators For example is is defined as an xfx operator which means a term like X is Y is 7 would cause a syntax error This makes sense because that term certainly
54. lve a complex problem provide the solution for the simplest problem of its kind and provide a rule for transforming such a complex problem into a slightly simpler problem In other words provide a solution for the base case and provide a recursion rule or step You then get an algorithm or program that solves every problem of this particular problem class Compare Using induction we prove a statement by going from a base case up through all cases Using recursion we compute a function for an arbitrary case by going through all cases down to the base case Recursive definition of functions The factorial n of a natural number n is defined as the product of all natural numbers from 1 to n Here s a more formal recursive definition also known as an inductive definition Ip gp base case n aN n 1 n forn gt 1 recursion rule To compute the actual value of say 5 we have to pass through the second part of that definition 4 times until we get to the base case and are able to calculate the overall result That s a recursion Recursion in Java Here s a Java method to compute the factorial of a natural num ber It is recursive for didactic reasons note that this is not the best way of implementing the factorial in Java public int factorial int n 1 if n 1 return 1 base case else return factorial n 1 n recursion step Recursion in Prolog The definition of a Prolog
55. m Cu INSTITUTE FOR LOGIC LANGUAGE AND COMPUTATION Lecture Notes An Introduction to Prolog Programming Ulle Endriss UNIVERSITEIT VAN AMSTERDAM by Ulle Endriss University of Amsterdam Email ulle illc uva n1 Version 7 July 2007 Preface These lecture notes introduce the declarative programming language Prolog The em phasis is on learning how to program rather than on the theory of logic programming Nevertheless a short chapter on the logic foundations of Prolog is included as well All examples have been tested using SWI Prolog www swi prolog org and can be ex pected to work equally well with most other Prolog systems These notes have originally been developed for a course I taught at King s College London in 1999 and 2000 Amsterdam August 2005 U E The present version corrects a number of minor errors in the text most of which have been pointed out to me by students following a course I have given at the University of Amsterdam in 2005 and 2006 Amsterdam July 2007 U E ii Contents 1 The Basics 1 1 1 Getting Started An Example 2 0 00 02 eee pr OOS SSH pte ae E x E eRe Re he ER ewe S 9 2 x s 4 bow CXOPHHS 2 99 05 20 9 13 8 9 RBRE TERE EORR BURN UR S S 4 1 2 2 Clauses Programs and Queries cles 5 1 2 3 Some Built in Predicates 6 1 3 Answering Queries 8 Peo Mathini x o 209 93x03 90x 2 atetareee anes dag 8 1 3 2
56. n becomes the new goal to be satisfied If the body consists of several predicates the goal is again split into subgoals to be executed in turn In other words the head of a rule is considered provably true if the conjunction of all 10 Chapter 1 The Basics its body predicates are provably true If a goal matches with a fact in our program the proof for that goal is complete and the variable instantiations made during matching are communicated back to the surface Note that the order in which facts and rules appear in our program is important here Prolog will always try to match its current goal with the first possible fact or rule head it can find If the principal functor of a goal is a built in predicate the associated action is exe cuted whilst the goal is being satisfied For example as far as goal execution is concerned the predicate write Hello World will simply succeed but at the same time it will also print the words Hello World on the screen As mentioned before the built in predicate true will always succeed without any further side effects whereas fail will always fail Sometimes there is more than one way of satisfying the current goal Prolog chooses the first possibility as determined by the order of clauses in a program but the fact that there are alternatives is recorded If at some point Prolog fails to prove a certain subgoal the system can go back and try an alternative way of executing the previous goal T
57. nd a variable is given in the second argument position i e as in item a Your explanations should include answers to the following questions What case s is are covered by the Prolog fact What effect has the cut in the first line of the program Why has the anonymous variable been used Exercise 5 3 Implement Euclid s algorithm to compute the greatest common divisor GCD of two non negative integers This predicate should be called gcd 3 and given two non negative integers in the first two argument positions should match the variable in the third position with the GCD of the two given numbers Examples gcd 57 27 X X 3 Yes Ulle Endriss And Introduction to Prolog Programming 4T gcd 1 30 X X 1 Yes gcd 56 28 X X 28 Yes Make sure your program behaves correctly also when the semicolon key is pressed Hints The GCD of two numbers a and b with a gt b can be found by recursively substituting a with b and b with the rest of the integer division of a and 6 Make sure you define the right base case s Exercise 5 4 Implement a Prolog predicate occurrences 3 to count the number of occurrences of a given element in a given list Make sure there are no wrong alternative solutions Example occurrences dog dog frog cat dog dog tiger N N23 Yes Exercise 5 5 Write a Prolog predicate divisors 2 to compute the list of all divisors for a given natural
58. nd argument is matched with the length of the list in the first argu ment Example length elephant 1 2 3 41 Length Length 3 Yes It is also possible to use length 2 with an uninstantiated first argument This will generate a list of free variables of the specified length length List 3 List _G248 _G251 G254 Yes The names of those variables may well be different every time you call this query because they are generated by Prolog during execution time member 2 The goal member Elem List will succeed if the term Elem can be matched with one of the members of the list List Example member dog elephant horse donkey dog monkey Yes append 3 Concatenate two lists This built in works exactly like the predicate concat lists 3 presented in Section 2 2 last 2 This predicate succeeds if its second argument matches the last element of the list given as the first argument of last 2 reverse 2 This predicate can be used to reverse the order of elements in a list The first argument has to be a fully instantiated list and the second one will be matched with the reversed list Example reverse 1 2 3 4 5 X X 5 4 3 2 1 Yes select 3 Given a list in the second argument and an element of that list in the first this predicate will match the third argument with the remainder of that list Example select bird mouse bird jellyfish zebra X
59. ns of the Prolog language These notes cover the most important Prolog concepts you need to know about but it is certainly worthwhile to also have a look at the literature The following three are well known titles but you may also consult any other textbook on Prolog e I Bratko Prolog Programming for Artificial Intelligence 3rd edition Addison Wesley Publishers 2001 e F W Clocksin and C S Mellish Programming in Prolog 5th edition Springer Verlag 2003 e L Sterling and E Shapiro The Art of Prolog 2nd edition MIT Press 1994 1 1 Getting Started An Example In the introduction it has been said that Prolog is a declarative or descriptive language Programming in Prolog means describing the world Using such programs means asking Prolog questions about the previously described world The simplest way of describing the world is by stating facts like this one 2 Chapter 1 The Basics bigger elephant horse This states quite intuitively the fact that an elephant is bigger than a horse Whether the world described by a Prolog program has anything to do with our real world is of course entirely up to the programmer Let s add a few more facts to our little program bigger elephant horse bigger horse donkey bigger donkey dog bigger donkey monkey This is a syntactically correct program and after having compiled it we can ask the Prolog system questions or queries in proper Prolog jargon about
60. number Example divisors 30 X X 1 2 3 5 6 10 15 30 Yes Make sure your program doesn t give any wrong alternative solutions and doesn t fall into an infinite loop when the user presses the semicolon key Exercise 5 6 Check some of your old Prolog programs to see whether they produce wrong alternative solutions or even fall into a loop when the user presses semicolon Fix any problems you encounter using cuts one will often be enough Chapter 6 Logic Foundations of Prolog From using expressions such as predicate true proof etc when speaking about Prolog programs and the way goals are executed when a Prolog system attempts to answer a query it should have become clear already that there is a very strong connection between logic and Prolog Not only is Prolog the programming language that is probably best suited for implementing applications that involve logical reasoning but Prolog s query resolution process itself is actually based on a logical deduction system This part of the notes is intended to give you a first impression of the logics behind Prolog We start by showing how basic Prolog programs can be translated into sets of first order logic formulas These formulas all have a particular form they are known as Horn formulas Then we shall briefly introduce resolution a proof system for Horn formulas which forms the basis of every Prolog interpreter 6 1 Translation of Pr
61. number n will return the nth element of that list Examples element at tiger dog teddy bear horse cow 3 X X teddy bear Yes element at a b c d 27 X No Exercise 3 5 Write a Prolog predicate mean 2 to compute the arithmetic mean of a given list of numbers Example mean 1 2 3 4 X X 2 5 Yes Exercise 3 6 Write a predicate range 3 to generate all integers between a given lower and a given upper bound The lower bound should be given as the first argument the upper bound as the second The result should be a list of integers which is returned in the third argument position If the upper bound specified is lower than the given lower bound the empty list should be returned Examples Ulle Endriss And Introduction to Prolog Programming 25 range 3 11 X X 3 4 5 6 7 8 9 10 11 Yes f range 7 4 X X Yes Exercise 3 7 Polynomials can be represented as lists of pairs of coefficients and ex ponents For example the polynomial Ax n y 27 can be represented as the following Prolog list Ek Ch 2 9 s Calo 27 0 Write a Prolog predicate poly sum 3 for adding two polynomials using that representa tion Try to find a solution that is independent of the ordering of pairs inside the two given lists Likewise your output doesn t have to be ordered Examples poly_sum 5 3 1 2 1 3 Sum Sum 6 3 1 2 Yes poly_sum
62. olog Clauses into Formulas This sections describes how Prolog clauses i e facts rules and queries can be translated into first order logic formulas We will only consider the very basic Prolog syntax here in particular we won t discuss cuts negation disjunction the anonymous variable or the evaluation of arithmetic expressions at this point Recall that given their internal representation using the dot functor see Section 2 1 lists don t require any special treatment at least not at this theoretical level Prolog predicates correspond to predicate symbols in logic terms inside the predicates correspond to functional terms appearing as arguments of logic predicates These terms are made up of constants Prolog atoms variables Prolog variables and function symbols Prolog functors All variables in a Prolog clause are implicitly universally quantified that is every variable could be instantiated with any Prolog term Given this mapping from Prolog predicates to atomic first order formulas the trans lation of entire Prolog clauses is straightforward Recall that can be read as if i e as an implication from right to left and that the comma separating subgoals in a clause constitutes a conjunction Prolog queries can be seen as Prolog rules with an empty AQ 50 Chapter 6 Logic Foundations of Prolog head This empty head is translated as L falsum Why this is so will become clear later When translating
63. onk then the predicate should fail Examples pp_analyse dog plink cat plink horse Principal operator plink Left sub term dog plink cat Right sub term horse Yes pp_analyse dog plonk cat plonk horse Principal operator plonk Left sub term dog Right sub term cat plonk horse Yes 7 pp analyse lion plink cat plonk monkey plonk cow Principal operator plonk Left sub term lion plink cat Right sub term monkey plonk cow Yes Exercise 4 2 Consider the following operator definitions op 100 fx the op 100 fx a op 200 xfx has a Indicate the structure of this term using parentheses and name its principal functor claudia has a car b What would Prolog reply when presented with the following query the lion has hunger Who has What c Explain why the following query would cause a syntax error X she has whatever has style Exercise 4 3 Define operators in Prolog for the connectives of propositional logic Use the following operator names Negation neg Ulle Endriss And Introduction to Prolog Programming 33 Conjunction and Disjunction or Implication implies Think about what precedences and associativity patterns are appropriate In particular your declarations should reflect the precedence hierarchy of the connectives as they are defined in propositional logic Define all binary logical operators as being left associative Your definitions s
64. rolog fails to derive a proof for Goal i e if Goal is not provably true T his semantics of the negation operator is known as negation as failure Prolog s negation is defined as the failure to provide a proof In real life this is usually not the right notion though it has been adopted by judicature innocent unless proven guilty Let s look at an example for the use of the operator Assume we have a list of Prolog facts with pairs of people who are married to each other married peter lucy married paul mary married bob juliet married harry geraldine Then we can define a predicate single 1 that succeeds if the argument given can neither be found as the first nor as the second argument in any of the married 2 facts We can use the anonymous variable for the other argument of married 2 because its value would be irrelevant Ulle Endriss And Introduction to Prolog Programming 43 single Person married Person _ married _ Person Example queries single mary No single claudia Yes Again we have to read the answer to the last query as Claudia is assumed to be single because she cannot shown to be married We are only allowed to shorten this interpretation to Claudia is single if we can be sure that the list of married 2 facts is exhaustive i e if we accept the closed world assumption for this example Now consider the following query and Prolog s response single
65. rolog system Built ins can be used in a similar way as user defined predicates The important difference between the two is that a built in predicate is not allowed to appear as the principal functor in a fact or the head of a rule This must be so because using them in such a position would effectively mean changing their definition Equality Maybe the most important built in predicate is equality Instead of writing expressions such as X Y we usually write more conveniently X Y Such a goal succeeds if the terms X and Y can be matched This will be made more precise in Section 1 3 Ulle Endriss And Introduction to Prolog Programming 1 Guaranteed success and certain failure Sometimes it can be useful to have predi cates that are known to either fail or succeed in any case The predicates fail and true serve exactly this purpose Consulting program files Program files can be compiled using the predicate consult 1 The argument has to be a Prolog atom denoting the particular pro gram file For example to compile the file big animals pl submit the following query to Prolog consult big animals pl If the compilation is successful Prolog will reply with Yes Otherwise a list of errors is displayed Output If besides Prolog s replies to queries you wish your program to have further output you can use the write 1 predicate The argument can be any valid Prolog term In the case of a variabl
66. s so we present it before describing what actually happens when a query is processed or more generally speaking when a goal is executed 1 3 1 Matching Two terms are said to match if they are either identical or if they can be made identical by means of variable instantiation Instantiating a variable means assigning it a fixed value Two free variables also match because they could be instantiated with the same ground term It is important to note that the same variable has to be instantiated with the same value throughout an expression The only exception to this rule is the anonymous vari able _ which is considered to be unique whenever it occurs We give some examples The terms is_bigger X dog and is bigger elephant dog match because the variable X can be instantiated with the atom elephant We could test this in the Prolog interpreter by submitting the corresponding query to which Prolog would react by listing the appropriate variable instantiations is bigger X dog is bigger elephant dog X elephant Yes The following is an example for a query that doesn t succeed because X cannot match with 1 and 2 at the same time p X 2 2 pL Y X No Ulle Endriss And Introduction to Prolog Programming 9 If however instead of X we use the anonymous variable _ matching is possible because every occurrence of _ represents a distinct variable During matching Y is instantiated with 2 SUDO 2 2 mpl Ys
67. t married In the old days he d simply have saddled his best horse to ride down to the valleys of say Essex and find himself the sort of young beautiful and intelligent girl he s after But obviously times have changed life in general is becoming much more complex these days and most importantly our prince is rather busy defending monarchy against communism anarchy democracy pick your favourite Fortunately his royal board of advisors consists of some of the finest psychologists and Prolog programmers in the With parent goal we mean the goal that caused the matching of the rule s head This story has been written with a British audience in mind Please adapt to your local circumstances Ulle Endriss And Introduction to Prolog Programming 39 country They form an executive committee to devise a Prolog program to automatise the prince s quest for a bride The task is to simulate as closely as possible the prince s decision if he actually were to go out there and look for her by himself From the expert psychologists we gather the following information e The prince is primarily looking for a beautiful girl But to be eligible for the job of a prince s wife she d also have to be intelligent e The prince is young and very romantic Therefore he will fall in love with the first beautiful girl he comes across love her for ever and never ever consider any other woman as a potential wife again Even if he can t
68. te the definition of add 3 as follows add Element List Result member Element List Result List add Element List Element List Try to understand how this solves the problem Note that from a declarative point of view the two versions of the program are equivalent but procedurally they behave differently So be careful with those cuts 5 2 Negation as Failure In the marriage example from before from the fact intelligent claudia not appear ing in the database we concluded that beautiful Claudia wasn t intelligent This touches upon an important issue of Prolog semantics namely that of negation 5 2 1 The Closed World Assumption In order to give a positive answer to a query Prolog has to construct a proof to show that the set of facts and rules of a program implies that query Therefore precisely speaking answering Yes to a query means not only that the query is true but that it is provably true Consequently a No doesn t mean the query is necessarily false just not provably true Prolog failed to derive a proof This attitude of negating everything that is not explicitly in the program or can be concluded from the information provided by the program is often referred to as the closed world assumption That is we think of our Prolog program as a little world of its own assuming nothing outside that world does exist is true 42 Chapter 5 Backtracking Cuts and Negation In everyday reasonin
69. th them 2 1 Notation Lists are contained in square brackets with the elements being separated by commas Here s an example elephant horse donkey dog This is the list of the four atoms elephant horse donkey and dog Elements of lists could be any valid Prolog terms i e atoms numbers variables or compound terms This includes also other lists The empty list is written as The following is another example for a slightly more complex list elephant X parent X tom La b c 22 Internal representation Internally lists are represented as compound terms using the functor dot The empty list is an atom and elements are added one by one The list a b c for example corresponds to the following term a COD Ce O 2 2 Head and Tail The first element of a list is called its head and the remaining list is called the tail An empty list doesn t have a head A list just containing a single element has a head namely that particular single element and its tail is the empty list A variant of the list notation allows for convenient addressing of both head and tail of a list This is done by using the separator bar If it is put just before the last term inside a list it means that that last term denotes another list The entire list is 15 16 Chapter 2 List Manipulation then constructed by appending this sub list to the list represented by the sequence of el
70. this relation If from now on we use is bigger instead of bigger in our queries the program will work as intended is bigger elephant monkey Yes Prolog still cannot find the fact bigger elephant monkey in its database so it tries to use the second rule instead This is done by matching the query with the head of the rule which is is bigger X Y When doing so the two variables get instantiated X elephant and Y monkey The rule says that in order to prove the goal is bigger X Y with the variable instantiations that s equivalent to is bigger elephant monkey Prolog has to prove the two subgoals bigger X Z and is_bigger Z Y again with the same variable instantiations This process is repeated recursively until the facts that make up the chain between elephant and monkey are found and the query finally succeeds How this goal execution as well as term matching and variable instantiation really work will be examined in more detail in Section 1 3 Of course we can do slightly more exiting stuff than just asking yes no questions Suppose we want to know what animals are bigger than a donkey The corresponding query would be is bigger X donkey Again X is a variable We could also have chosen any other name for it as long as it starts with a capital letter The Prolog interpreter replies as follows is bigger X donkey X horse Horses are bigger than donkeys The query has succeeded but in order to
71. ts that allows for more efficient implementations Furthermore some extensions to the syntax of Prolog programs will be discussed Besides conjunction remember a comma separating two subgoals in a rule body represents a conjunction we shall introduce negation and disjunction 5 1 Backtracking and Cuts In Chapter 1 the term backtracking has been mentioned already Next we are going to examine backtracking in some more detail note some its useful applications as well as problems and discuss a way of overcoming such problems by using so called cuts 5 1 1 Backtracking Revisited During proof search Prolog keeps track of choicepoints i e situations where there is more than one possible match Whenever the chosen path ultimately turns out to be a failure or if the user asks for alternative solutions the system can jump back to the last choicepoint and try the next alternative This is process is known as backtracking It is a crucial feature of Prolog and facilitates the concise implementation of many problem solutions Let s consider a concrete example We want to write a predicate to compute all possible permutations of a given list The following implementation uses the built in predicate select 3 which takes a list as its second argument and matches the first argument with an element from that list The variable in the third argument position will then be matched with the rest of the list after having removed the chosen el
72. usly proposed pro gram by inserting a cut after the first subgoal inside the body of the first rule the rest remains exactly the same as before remove_duplicates remove duplicates Head Tail Result member Head Tail remove_duplicates Tail Result remove_duplicates Head Tail Head Result remove_duplicates Tail Result Now whenever the head of a list is a member of it s tail the first subgoal of the first rule Le member Head Tail will succeed Then the next subgoal will also succeed Without that cut it would be possible to backtrack that is to match the original goal with the head of the second rule to search for alternative solutions But once Prolog went past the cut this isn t possible anymore alternative matchings for the parent goal will not be tried Using this new version of the predicate remove_duplicates 2 we get the desired behaviour When asking for alternative solutions by pressing we immediately get the right answer namely No remove duplicates a b b c a List List b c al No Now we are ready for a more precise definition of cuts in Prolog Whenever a cut is encountered in a rule s body all choices made between the time that rule s head has been matched with the parent goal and the time the cut is passed are final i e any choicepoints are being discarded Let s exemplity this with a little story Suppose a young prince wants to ge
73. would have to execute the following four queries true and true Yes 7 true and false No 7 false and true No Ulle Endriss And Introduction to Prolog Programming 45 false and false No Hence the corresponding truth table would look as follows One more example before we start writing the actual program true and true and false implies true and neg false Yes In the examples we have used the Prolog atoms true and false The former is actually a built in predicate with exactly the meaning we require so that s fine And our false should behave just as the built in fail the only difference is the name So the Prolog rule for false is quite simple false fail Next are conjunction and disjunction They obviously correspond to the Prolog opera tors comma and semicolon respectively We use the built in predicate call 1 to invoke the subformulas represented by the variables as Prolog goals and A B call A call B or A B call A call B Our own negation operator neg again is just another name for the built in V Operator neg A call A Defining implication is a bit more tricky One way would be to exploit the classical equivalence of A B z A V B and define implies in terms of or and neg A somewhat nicer solution this admittedly depends on one s sense of aesthetics however would be to use a cut Like this implies A B call A

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