A Clause Learning Algorithm Combining Immune Mechanism to Invent Predicate

Aiming at the larger search space of learning clause in Inductive Logic Programming, we put forward the definitions of the predicate template and the clause template to reduce search space. We suggest IMPI algorithm, which is a genetic algorithm combining immune mechanism and uses the clause template as genetic code to learn the clause template of required clause. IMPI uses immune mechanism to invent new predicates, which can extend the hypothesis language, find better results. Correspondingly we design when to invent predicates. After obtaining the clause template, we use a general method based on generalization and information gain sampling to convert clause template to clause. We design the corresponding fitness function and genetic operator. It indicates that this algorithm can reduce the search space, improve the efficiency of search algorithm and can learn recursion clause by theoretical analysis and experiment comparison. It is an effective clause learning algorithm.