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Application of Methods of Adaptive Learning to the Problem of Automatic Decision Making Under Conditions of a Priori Uncertainty

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Proceedings of the Fourth International Joint Conference on Artificial Intelligence. Learning Debugging And Automatic Programming. Pages 223-224.

Abstract

The paper deals with the adaptive approach to decision making as applied to the problema ot biological and medical cybernetics characterised by a priori Wlcertain ty. A number ot algorithms is suggested which, being baaed on the analisis ot apoateriorJ information yield the most adequate decision rule to a specific problem. The learning is achieved b.1 the stochastic approximation method and by means ot the correction ot the decision rule structure The methods discussed have been realized on a computer and used in a cybernetic medical centre.

V. Akhutin, M. Ioffe, G. Kotler, and A. Rats. 1975. Application of Methods of Adaptive Learning to the Problem of Automatic Decision Making Under Conditions of a Priori Uncertainty. In Proceedings of the Fourth International Joint Conference on Artificial Intelligence, IJCAI-75. IJCAI, 223–224. https://ijcai.org/proceedings/1975/34
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