A Consideration on the Learning Performances of the Hierarchical Structure Learning Automata (HSLA) Operating in the General Nonstationary Multiteacher Environment

摘要

Learning behaviors of the hierarchical structure learning automata (HSLA) with the three representative algorithms under the non-stationary multiteacher environments are considered. Several computer simulations confirm the effectiveness of the newly developed relative reward strength algorithm (NRRSA).