A Training Algorithm for Systems Described by Stochastic Transition Matrices

Robert M. Glorioso, Grant Grueneich · IEEE Transactions on Systems Man and Cybernetics · 1971

Stochastic transition matrices are a convenient means for describing the behavior of adaptive and learning systems. Several systems which utilize these matrices and associated reinforcement (reward and punishment) techniques have been reported. A training algorithm is described which has been applied to a learning system described by stochastic transition matrices in which the environment was unknown a priori and nonstationary.

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