%% this is a planning problem from C. Elkan, "Incremental Approximate %% Planning: Abductive Default Reasoning, AAAI Spring Symposium on %% Automated Abduction, 1990. %% holds(proposition,state). %% causes(action,state,new_state). %% can(action,state). %% initial state of the world. holds(in(christian,arena),s0). holds(in(lion,cage),s0). holds(in(trainer,cage),s0). %% rules for how the world evolves: holds(P,do(S,A)) :- causes(A,S,P). holds(P,do(S,A)) :- nonvar(S), holds(P,S), \+ cancels(A,S,P). % if you are eating an X, then the X is where you are. holds(in(X,H),S) :- holds(eats(lion,X),S), holds(in(lion,H),S). %% the effects of actions: causes(pounce(lion,X),S,eats(lion,X)) :- can(pounce(lion,X),S). causes(jump(X),S,in(X,arena)) :- can(jump(X),S), holds(in(X,cage),S). cancels(drop(X,Y),S,eats(X,Y)) :- can(drop(X,Y),S). %% preconditions on actions. can(pounce(X,Y),S) :- holds(in(X,L),S), holds(in(Y,L),S), X\==Y, \+ holds(eats(X,_),S). can(jump(lion),S) :- holds(eats(lion,trainer),S). can(drop(X,Y),S) :- holds(eats(X,Y),S). query :- holds(eats(lion,christian),State).