Hybal: A Self Tutoring Algorithm for Concept Learning in Highly Autonomous Systems

In the paper, a hybrid learning algorithm for discovering concepts with multiple disjuncts in an exponentially growing hypothesis space is presented. The approach, HYBAL, extends the work of Hirsh 141 and Reynolds [9] to produce an autonomous system that learns to partition a large search space incrementally into successively smaller search spaces using a divide and conquer strategy. This approach is used to solve the Boolean problem for a F20 multiplexor. The system needed to examine less than 0.5% of the entire search space, in order to achieve a solution.