Learning Behaviors of the Hierarchical Structure Learning Automata Operating in the General Nonstationary Multiteacher Environment

抄録

A new learning algorithm for the hierarchical structure learning automata operating in the nonstationary multiteacher environment is proposed. It is shown that the proposed algorithm ensures convergence with probability 1 to the optimal path under a certain type of nonstationary multiteacher environment. The efficacy of the proposed algorithm is demonstrated by the several computer simulation studies below.