A New Nonlinear Reinforcement Scheme for Stochastic Learning Automata
نویسندگان
چکیده
Reinforcement schemes represent the basis of the learning process for stochastic learning automata, generating their learning behavior. An automaton using a reinforcement scheme can decide the best action, based on past actions and environment responses. The aim of this paper is to introduce a new reinforcement scheme for stochastic learning automata. We test our schema and compare with other nonlinear reinforcement schemes. The results reveal a faster convergence of the new schema to the „optimal” action. Key-Words: Stochastic Learning Automata, Reinforcement Scheme
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