Let me start by saying that this question can possibly be answered by AI wizards with no Prolog experience.
The excellent Prolog Programming for Artificial Intelligence book has this quite terse and clever minimax implementation:
minimax( Pos, BestSucc, Val) :-
moves( Pos, PosList), !, % Legal moves in Pos produce PosList
best( PosList, BestSucc, Val)
;
staticval( Pos, Val). % Pos has no successors: evaluate statically
best( [ Pos], Pos, Val) :-
minimax( Pos, _, Val), !.
best( [Pos1 | PosList], BestPos, BestVal) :-
minimax( Pos1, _, Val1),
best( PosList, Pos2, Val2),
betterof( Pos1, Val1, Pos2, Val2, BestPos, BestVal).
betterof( Pos0, Val0, Pos1, Val1, Pos0, Val0) :- % Pos0 better than Pos1
min_to_move( Pos0), % MIN to move in Pos0
Val0 > Val1, ! % MAX prefers the greater value
;
max_to_move( Pos0), % MAX to move in Pos0
Val0 < Val1, !. % MIN prefers the lesser value
betterof( Pos0, Val0, Pos1, Val1, Pos1, Val1). % Otherwise Pos1 better than Pos0
However, the author didn't go to much length in describing it and I'm left to wonder what min_to_move/1
and max_to_move/1
are.
Can anyone explain these to me?
Thanks in advance!