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B – Tree search reinforcment learning for model based intelligent agent

Publisher : Proceedings of SPIE - The International Society for Optical Engineering

Campus : Coimbatore

School : School of Engineering

Year : 2013

Abstract : Agents trained by learning techniques provide a powerful approximation of active solutions for naive approaches. In this study using B - Trees implying reinforced learning the data search for information retrieval is moderated to achieve accuracy with minimum search time. The impact of variables and tactics applied in training are determined using reinforcement learning. Agents based on these techniques perform satisfactory baseline and act as finite agents based on the predetermined model against competitors from the course. © 2013 SPIE.

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