A New Learning Algorithm for the Hierarchical Structure Learning Automata Operating in the General Nonstationary Multiteacher Environment

摘要

Learning behaviors of the hierarchical structure stochastic automata operating in the general nonstationary multiteacher environment are considered. It is shown that convergence with probability 1 to the optimal path is ensured by a new learning algorithm which is an extended form of the relative reward strength algorithm.