Learning about a path in a graph.

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

Program source code: graph_path_learning.pl

% Figure 19.9  Learning about a path in a graph.
 
 
% Learning about path: path(StartNode,GoalNode,Path)
 
% A directed graph
 
link(a,b).
link(a,c).
link(b,c).
link(b,d).
link(d,e).
 
backliteral( link(X,Y), [ X:item], [ Y:item]). 
backliteral( path(X,Y,L), [ X:item], [ Y:item, L:list]).
 
term( list, [X|L], [ X:item, L:list]).
term( list, [], []).
 
prolog_predicate( link(X,Y)).
 
start_clause( [ path(X,Y,L)] / [X:item,Y:item,L:list] ).
 
% Examples
 
ex( path( a, a, [a])).
ex( path( b, b, [b])).
ex( path( e, e, [e])).
ex( path( f, f, [f])).
ex( path( a, c, [a,c])).
ex( path( b, e, [b,d,e])).
ex( path( a, e, [a,b,d,e])).
 
nex( path( a, a, [])).
nex( path( a, a, [b])).
nex( path( a, a, [b,b])).
nex( path( e, d, [e,d])).
nex( path( a, d, [a,b,c])).
nex( path( a, c, [a])).
nex( path( a, c, [a,c,a,c])).
nex( path( a, d, [a,d])).