A new learning algorithm for the hierarchical structure learning automata operating in the nonstationary S-model random environment.
An extended algorithm of the relative reward strength algorithm is proposed. It is shown that the proposed algorithm ensures the convergence with probability I to the optimal path under the certain type of nonstationary environment. Several computer simulation results confirm the effectiveness of the proposed algorithm.
Baba
N
N
Dept. of Inf. Sci., Osaka Kyoiku Univ., Kashiwara, Japan.
Mogami
Y
Y