A bidirectional ILP algorithm
Markus Wiese · 1996
. The paper presents an approach for using a bidirectional search strategy for inductively learning clauses in a restricted first-order language. The learning target is to find a set of goal clauses that describes the true ground facts of the target predicate. In our example setting we further assume that the background knowledge is also given in the form of true (and false) ground facts for each background predicate. By fixing the number of variables allowed in the derived clauses we show that no explicit negative goal facts are needed in the case of the closed-world assumption since the rules are evaluated from the premise to the head rather than binding the variables of the goal literal first. As a consequence we get an efficient algorithm that tries to minimize the tuples of variable substitutions stored at each step of our covering approach. Introduction The paper presents an approach for using a bidirectional search strategy for inductively learning clauses in a restricted first...