The object level in Prolog. Meta-level predicates and operators. Contents. The flow of computation. The meta level in Prolog

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1 Lecture 8 Meta-level predicates and operators Contents Object level vs. meta level Controlling flow of computation Checking and dismantling expressions Comparison operators The object level in Prolog Prolog is used to handle information about: basic objects, usually represented by atoms (symbols, numbers); structures made up of basic objects or of other structures, represented as functor-argument expressions; relations between basic objects and/or structures, represented by predicates. Computations consist of (roughly speaking): checking if a clause in the program unifies with the current goal; if there is one, working through the body as goals; if t, failing. Introduction to Artificial Intelligence Programming, School of Informatics 2 The meta level in Prolog The flow of computation There are various built-in predicates and operators which: modify the basic clause-match flow of computation; allow checks on the form of a piece of Prolog; dismantle data-structures and (re)assemble them. The cut (!) : see earlier lecture. fail : this built-in predicate ( arguments) always fails. (Not strictly meta-level). true : this built-in predicate ( arguments) succeeds initially, but t on REDO (backtracking). (Not strictly meta-level).?- true, write( ), nl, fail. Introduction to Artificial Intelligence Programming, School of Informatics 3 Introduction to Artificial Intelligence Programming, School of Informatics 4

2 The flow of computation: repeat An example of repeat repeat : this built-in predicate ( arguments) succeeds initially, and also on every REDO (backtracking). Hence causes a constant re-calling of whatever is to the right of it.?- repeat, write( ), nl, fail.... <indefinite loop> Can be used to set up repetitions, but care is needed to find a way to stop the loop. This reads terms from standard input, stopping when the atom goodbye is encountered. readon:- repeat, read(goodbye). (The built-in read reads a single Prolog term, and unifies its argument with that value.) The following does the same, recursively: readmore:- read(c),!, doitem(c). doitem(goodbye):-!. doitem(_) :- readmore. % succeed if end % else continue (Both versions have a loophole, to be fixed later.) Introduction to Artificial Intelligence Programming, School of Informatics 5 Introduction to Artificial Intelligence Programming, School of Informatics 6 Flow of computation: call An example with call call/1: This takes one argument which should be in the form of a goal (i.e. a single term). It invokes its arguments as a goal, and success/failure depends on success/failure of that goal.?- call(write( )). This can be useful if data is to be manipulated (e.g. built up from smaller parts) then invoked as a goal (see later).?- timidcall. What do you want to do? write( Help ). Are you sure?. OK, here goes Help timidcall:- write( What do you want to do? ), read(goal), doublecheck(goal). doublecheck(goal):- write( Are you sure? ), read(response), maybedo(response, Goal). maybedo(, G):- write( OK, here goes ), nl, call(g). maybedo(, _G):- write( Fine, problem ). Introduction to Artificial Intelligence Programming, School of Informatics 7 Introduction to Artificial Intelligence Programming, School of Informatics 8

3 Negation Negation as igrance Notation: in Clocksin and Mellish, t. in Sicstus Prolog, \+ A prefix operator brackets round its argument are t necessary.?- \+ a = b.?- \+ a = a. This is t strictly genuine logical negation it means fail if this succeeds, succeed if this fails. E.g.?- father(john, mike). could mean there is information about the father predicate and arguments john, mike. It does t guarantee that there is explicit information to indicate that the father relation does t hold between these items. Similarly:?- \+ father(john, mike). does t indicate definite information that the relation does t hold it merely shows the absence of information that the relation does hold. Negation as failure The closed world assumption Introduction to Artificial Intelligence Programming, School of Informatics 9 Introduction to Artificial Intelligence Programming, School of Informatics 10 Examining Prolog terms var Examining Prolog terms =.. var/1: Succeeds if its argument is an uninstantiated variable, fails otherwise.?- var(x).?- X = a, var(x). The bug in readon and readmore earlier if the input item was a variable, it would unify with the end-marker goodbye and cause a false detection of the end. Possible fix to readon : readon:- repeat, read(x), \+ var(x), X = goodbye. To dismantle a term into its functor and its arguments, or to assemble a term from functor and arguments, use =..?- father(john, mike) =.. Info. Info = [father,john,mike]??- Term =.. [between, 3, 4, X]. Term = between(3,4,x)? If going from list of parts into a functor-argument term, the first item (the functor) must t be a variable. Possible fix to readmore rewrite first clause of doitem : doitem(x):- \+ var(x), X = goodbye. Introduction to Artificial Intelligence Programming, School of Informatics 11 Introduction to Artificial Intelligence Programming, School of Informatics 12

4 Example of assembling a goal More term manipulation: functor/3 % Reads data in from the user, then calls % the goal thus specified. callfromparts:- write( Supply predicate to be called ), read(p), write( Supply arguments to use ), collectargs(listofargs), Goal =..[P Listofargs], write( Term assembled ),nl, write( About to call goal... ),!, % If goal fails, don t re-read call(goal). (Assuming that collectargs/1 reads a list of items from the user.) functor/3: relates a term (arg 1) to its functor (arg 2) and the number of arguments the term has (arg 3). Either to dissect a term:?- functor(father(john, mike), F, M). F = father, M = 2? Or to construct an term with unbound arguments:?- functor(term, between, 3). Term = between(_a,_b,_c)? Introduction to Artificial Intelligence Programming, School of Informatics 13 Introduction to Artificial Intelligence Programming, School of Informatics 14 More term manipulation: arg/3 Comparison operator: negated unification arg/3: Given a term and an integer N, selects the Nth argument:?- arg(2, father(john, mike), Thevalue). Thevalue = mike? Does t work the other way round: the argument-number and the term must be supplied as values. If arg-number too big, just fails (t an error). \= : Fails if its arguments unify, succeeds if they don t.?- a(b,c) \= a(x, Y).?- a(b,c) \= a(x, Y, Z). true? Notice the true when there are variables in the goal, but bindings are supplied, despite the goal succeeding. Introduction to Artificial Intelligence Programming, School of Informatics 15 Introduction to Artificial Intelligence Programming, School of Informatics 16

5 Comparison operator strict identity Comparison operator negated identity == : Succeeds if its arguments are identical, with a variable matching only itself or an already sharing variable.?- f(a) == f(a).?- f(a) == f(b).?- A == B.?- A = B, B = C, A == C. B = A, C = A? \== : succeeds if == fails, fails if == succeeds.?- f(a) \== f(a).?- f(a) \== f(b).?- A \== B. true??- A = B, B = C, A \== C. Introduction to Artificial Intelligence Programming, School of Informatics 17 Introduction to Artificial Intelligence Programming, School of Informatics 18 Summary There are built-in predicates and operators that go outside the basic object-level. Some of these affect the flow of processing. Some are data-structure manipulations. There are also some comparison operators. Introduction to Artificial Intelligence Programming, School of Informatics 19