Syntax and Meaning of Prolog Programs

1. Syntax and Meaning of Prolog Programs Notes for Ch.2 of Bratko For CSCE 580 Sp03 Marco Valtorta

2. Data Objects • The typing system of Prolog is simple • Data objects include: • simple objects • constants • atoms • numbers • variables • structures

3. Atoms • strings of letters, digits, and underscore, starting with a lower-case letter • string of special characters (e.g., ====>) • (Some are predefined!) • strings of characters enclosed in single quotes (e.g., ‘Tim’, ‘c:\Marco\foo.pl’)

4. Numbers • Integers • limits are implementation dependent. • ?-current_prolog_flag( X,Y) gives 2147483647 and –2147483648 (32 bits) • Real numbers: • Rarely used • float: Computers cripled (sic) representation of a real number. Represented as ‘IEEE double’ (SWI-Prolog manual, p.234 [glossary of terms])

5. Variables • Strings of letters, digits, and underscore characters, starting with an upper-case (capital) letter or an underscore character • The underscore by itself is the anonymous variable, e.g.: • has_a_child( X) :- parent ( X,Y). is equivalent to • has_a_child(X) :- parent( X,_).

6. Scope of Variables • Each underscore represents a new anonymous variable: • someone_has_child :- parent( _,_). is equivalent to • someone_has_child :- parent( X,Y). and not equivalent to • someone_has_child :- parent( X,X). • The lexical scope of all other (named) variables is one clause

7. Structures • Structures are data objects that have several components • The components are combined by functors • date( 1, may, 2001) • date( Day, may, 2001) • segment( point( 1,1), point( 2,3)) • move( state( P1, onfloor, P1, H), push( P1,P2), state( P2,onfloor,P2,H) The first three denote objects, the last one denotes a predicate

8. Terms • Syntactically, all Prolog data objects are terms • A term is either • a simple object, or • a structure, i.e., a functor followed by “(“, one or more terms separated by commas, and “)” • Structures are conveniently represented by trees • actually, any term may be represented by a tree

9. Examples of Structures • point( 1,1) • T = triangle( point( 4,2), point(6,4), point( 7,1)) • There are two different functors in point( X,Y) and point( X,Y,Z): point/2 (a functor of arity 2) and point/3 (a functor of arity 3) • *( +( a,b), -(c,5)) may represent (a+b)*(c-5) • infix notation is possible and will be described in Ch.3 • par( r1, seq( par( r2,r3), r4))) • resistive circuit example in Figure 2.6(d)

10. Matching • Two terms match if • (1) they are identical, or • (2) the variables in both terms may be instantiated in such a way that after the substitution of variables by these objects the terms become identical • E.g., date( D,M,2001) and date( D1,may,Y1) match with the unifier {D/D1,M/may,Y1/2001} • Replace D with D1 everywhere in the two terms, then replace M with may, then replace Y1 with 2001

11. Most General Unifier ?-date( D,M,2001) = date( D1,may,Y1), date( D,M,2001) = date( 15,M,Y). • The first goal succeeds with most general unifier (mgu) g1 = {D/D1, M/may, Y1/2001}; then, we try to match date( D1,may,2001) and date( 15,may,Y) • This succeeds with mgu g2 = {D1/15, Y/2001} • Composition of g1 and g2 (g1 o g2) gives {D/15, M/may, Y1/2001, D1/15, Y/2001}

12. Algorithm to Find MGU for Terms • If S and T are constants, they match only if they are identical • If S is a variable and T is anything, check whether T contains S; if so, fail; if not, substitute T for S; and conversely • If S and T are structures, they match only if • they have the same principal functor • all corresponding components match • Example: Figure 2.7

13. Computing by Matching • ch2_1.pl: vertical( seg( point( X,Y), point( X,Y1))). horizontal( seg( point( X,Y), point( X1,Y))). 1 ?- vertical( seg( point(1,1), point(1,2))). Yes 2 ?- !!. vertical( seg( point(1,1), point(1,2))). Yes 3 ?- ^point(1,2)^point(2,Y). vertical( seg( point(1,1), point(2,Y))). No • Imagine how more difficult this would be in Java!

14. More Matching Examples ?-vertical( seg( point( 2,3), P). P = point( 2,Y) • 2 ?- vertical( seg( point(2,3), P)). P = point(2, _G409) • fresh variables are used in each copy of a clause ?-vertical(S), horizontal(S). S = seg( point(X,Y),point(X,Y)) • a point is the only (degenerate) segment that is both horizontal and vertical • 1 ?- vertical(S), horizontal(S). S = seg(point(_G391, _G392), point(_G391, _G392)) ;

15. Declarative Meaning of Prolog Programs • P :- Q, R. • Declarative readings: • P is true if Q and R are true • From Q and R follows P • Procedural readings: • To solve problem P, first solve subproblem Q, then solve subproblem R • To satisfy P, first satisfy Q, and then R

16. Declarative Meaning • An instance of a clause is the clause with each of its variable substituted by a term • A goal G is true if and only if: • there is a clause C in the program such that • there is a clause instance I of C such that • the head of I is identical to G, and • all the goals in the body of G are true • A query is true if all of its goals are true for the same instantiation of the variables

17. Semicolon (Or) • P :- Q; R. stands for P :- Q. P :- R. • P :- Q,R;S,T,U. stands for P :- (Q,R); (S,T,U). which is the same as P :- Q,R. P :- S,T,U. • In Prolog, disjunctions may only appear in the body (premise) of a rule, not in its head (conclusion).

18. Examples • Exercise 2.6: ch2_2.pl

19. Procedural Meaning • Sample trace of the procedure execute: • program of Figure 2.10 (in ch2_3.pl) • query: ?-dark( X), big( X). • Use the Prolog tracer • non-graphical (nonguitracer/0) • graphical (PCE-based: guitracer/0) • I find the non-graphical tracer clearer on this example

20. The Procedure execute program success/failure indicator execute goal list instantiation of variables

21. execute • English description: Box on p.42 • Pseudocode: Figure 2.11 • The instantiation returned is the one that leads to successful termination • If a recursive call to execute fails, backtracking occurs, and variable instantiations done after the failure point are undone • Hashing (at least on functors) is used to reduce scanning

22. Monkey and Banana • A classic example of a puzzle-style problem (task environment is observable, deterministic, single-agent, static, etc.) • The program solves the problem by search • state has four components: • monkey’s horizontal position (atdoor, middle, atwindow) • monkey’s vertical position (onfloor, onbox) • horizontal position of the box (atdoor, middle, atwindow) • whether the monkey has the banana (has, hasnot)

23. Moves • There are four types of actions (moves), which change the state of the environment: • grasp banana • climb box • push box • walk around • These are formalized by the relation move( State1, Move, State2), where State1 and State2 are the states before and after the Move

24. Two Moves • A simple move: move( state( middle, onbox, middle, hasnot),%pre grasp, %move state( middle, onbox, middle, has) ). %post • A move schema: move( state( Pos1, onfloor, Box, Has), %state before walk( Pos1, Pos2), %move state( Pos2, onfloor, Box, Has) ). %state after

25. Can the Monkey Get the Banana? • If the monkey has the banana, it can get it: canget( state( _,_,_,has) ). • If the monkey does not have the banana, it can get it if it can move to a state in which it can get the banana: canget( State1) :- move( State1, Move, State2), canget( State2). • See Figure 2.13 (graph)

26. Monkey and Banana Program • Figure 2.14. Try: ?-canget( state( atdoor, onfloor, atwindow,hasnot) ). • Goal tree for this goal is shown in Figure 2.15: • Prolog backtracks only once • Why does Prolog try the moves in the order indicated? • The order of clauses is crucial

27. Danger of Infinite Looping • p :- p. ?-p. • If we place the walk rule before the climb and push rules (program fig2_14ord.pl), the monkey will walk aimlessly and never get the banana: ?- canget(state(atdoor,onfloor,atwindow,hasnot)). ERROR: Out of local stack • Tracing indicates a repeated goal • There are more principled ways to prevent infinite looping in search, as we will see in Ch.11

28. Variations on Predecessor • The variations (in program ch2_16.pl, in which I included the parent relation) are obtained by reordering goals or clauses of the original • pred1 and pred2 always work • pred4 fails on, e.g., ?-pred4(tom,pat) • pred3 fails on, e.g., ?-pred3(liz,jim) • pred1 is “simplest”: it tries the simplest options first

29. Combining Declarative and Procedural Views • The order of clauses and goals matters • Some declaratively correct Prolog programs do not work in practice • Should we forget about the declarative meaning of Prolog programs? • No! Declarative aspects are easier to formulate and understand • First concentrate on the declarative aspects of a problem, then address the procedural aspects as needed