A best-first search program.

Source: PROLOG programming for artificial intelligence, 3rd Edition, Harlow, 2001, ISBN 0-201-40375-7.


Program source code:


% Figure 12.3  A best-first search program.
:- op( 900, fy, not).
% not Goal): negation as failure; 
%   Note: This is often available as a built-in predicate,
%   often written as prefix operator "\+", e.g. \+ likes(mary,snakes)
not Goal  :-
  Goal, !, fail
% bestfirst( Start, Solution): Solution is a path from Start to a goal
bestfirst( Start, Solution) :-
  expand( [], l( Start, 0/0),  9999, _, yes, Solution).
	%  Assume 9999 is greater than any f-value
% expand( Path, Tree, Bound, Tree1, Solved, Solution):
%   Path is path between start node of search and subtree Tree,
%   Tree1 is Tree expanded within Bound,
%   if goal found then Solution is solution path and Solved = yes
%  Case 1: goal leaf-node, construct a solution path
expand( P, l( N, _), _, _, yes, [N|P])  :-
%  Case 2: leaf-node, f-value less than Bound
%  Generate successors and expand them within Bound.
expand( P, l(N,F/G), Bound, Tree1, Solved, Sol)  :-
  F  =<  Bound,
  (  bagof( M/C, ( s(N,M,C), not member(M,P) ), Succ), 
     !,                                    % Node N has successors
     succlist( G, Succ, Ts),               % Make subtrees Ts
     bestf( Ts, F1),                       % f-value of best successor
     expand( P, t(N,F1/G,Ts), Bound, Tree1, Solved, Sol)
     Solved = never                        % N has no successors - dead end
  ) .
%  Case 3: non-leaf, f-value less than Bound
%  Expand the most promising subtree; depending on 
%  results, procedure continue will decide how to proceed
expand( P, t(N,F/G,[T|Ts]), Bound, Tree1, Solved, Sol)  :-
  F  =<  Bound,
  bestf( Ts, BF), min( Bound, BF, Bound1),          % Bound1 = min(Bound,BF)
  expand( [N|P], T, Bound1, T1, Solved1, Sol),
  continue( P, t(N,F/G,[T1|Ts]), Bound, Tree1, Solved1, Solved, Sol).
%  Case 4: non-leaf with empty subtrees
%  This is a dead end which will never be solved
expand( _, t(_,_,[]), _, _, never, _) :- !.
%  Case 5:  f-value greater than Bound
%  Tree may not grow.
expand( _, Tree, Bound, Tree, no, _)  :-
  f( Tree, F), F > Bound.
% continue( Path, Tree, Bound, NewTree, SubtreeSolved, TreeSolved, Solution)
continue( _, _, _, _, yes, yes, Sol).
continue( P, t(N,F/G,[T1|Ts]), Bound, Tree1, no, Solved, Sol)  :-
  insert( T1, Ts, NTs),
  bestf( NTs, F1),
  expand( P, t(N,F1/G,NTs), Bound, Tree1, Solved, Sol).
continue( P, t(N,F/G,[_|Ts]), Bound, Tree1, never, Solved, Sol)  :-
  bestf( Ts, F1),
  expand( P, t(N,F1/G,Ts), Bound, Tree1, Solved, Sol).
% succlist( G0, [ Node1/Cost1, ...], [ l(BestNode,BestF/G), ...]):
%   make list of search leaves ordered by their F-values
succlist( _, [], []).
succlist( G0, [N/C | NCs], Ts)  :-
  G is G0 + C,
  h( N, H),                             % Heuristic term h(N)
  F is G + H,
  succlist( G0, NCs, Ts1),
  insert( l(N,F/G), Ts1, Ts).
% Insert T into list of trees Ts preserving order w.r.t. f-values
insert( T, Ts, [T | Ts])  :-
  f( T, F), bestf( Ts, F1),
  F  =<  F1, !.
insert( T, [T1 | Ts], [T1 | Ts1])  :-
  insert( T, Ts, Ts1).
% Extract f-value
f( l(_,F/_), F).        % f-value of a leaf
f( t(_,F/_,_), F).      % f-value of a tree
bestf( [T|_], F)  :-    % Best f-value of a list of trees
  f( T, F).
bestf( [], 9999).       % No trees: bad f-value
min( X, Y, X)  :-
  X  =<  Y, !.
min( X, Y, Y).


pl/prolog/pllib/best-first.txt · ostatnio zmienione: 2019/06/27 15:50 (edycja zewnętrzna) Valid CSS Driven by DokuWiki do yourself a favour and use a real browser - get firefox!! Recent changes RSS feed Valid XHTML 1.0