14 March 2013 B-tree search reinforcement learning for model based intelligent agent
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Proceedings Volume 8768, International Conference on Graphic and Image Processing (ICGIP 2012); 87686F (2013) https://doi.org/10.1117/12.2021162
Event: 2012 International Conference on Graphic and Image Processing, 2012, Singapore, Singapore
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.
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S. Bhuvaneswari, S. Bhuvaneswari, R. Vignashwaran, R. Vignashwaran, } "B-tree search reinforcement learning for model based intelligent agent", Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87686F (14 March 2013); doi: 10.1117/12.2021162; https://doi.org/10.1117/12.2021162
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