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Optimal non-linear reinforcement schemes for stochastic automata

Lakshmivarahan, S and Thathachar, MAL (1972) Optimal non-linear reinforcement schemes for stochastic automata. In: Information Sciences, 4 (2). pp. 121-128.

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Official URL: http://dx.doi.org/10.1016/0020-0255(72)90008-4

Abstract

Two optimal non-linear reinforcement schemes—the Reward-Inaction and the Penalty-Inaction—for the two-state automaton functioning in a stationary random environment are considered. Very simple conditions of symmetry of the non-linear function figuring in the reinforcement scheme are shown to be necessary and sufficient for optimality. General expressions for the variance and rate of learning are derived. These schemes are compared with the already existing optimal linear schemes in the light of average variance and average rate of learning.

Item Type: Journal Article
Publication: Information Sciences
Publisher: Elsevier Science
Additional Information: Copyright of this article belongs to Elsevier Science.
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 24 Jun 2010 09:33
Last Modified: 24 Jun 2010 09:33
URI: http://eprints.iisc.ac.in/id/eprint/28601

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