Efficient fast learning automata

A new class of learning automata which are capable of supporting high-speed real-time applications is introduced. The proposed learning automata have a unique characteristic: they are capable of performing both probability updating and action selection with a computational complexity which is independent of the number of actions. Apart from their low computational complexity, the proposed automata are capable of achieving a high performance when operating in non-stationary stochastic environments.

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