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Proceedings Paper

B-tree search reinforcement learning for model based intelligent agent
Author(s): S. Bhuvaneswari; R. Vignashwaran
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Paper 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.

Paper Details

Date Published: 14 March 2013
PDF: 4 pages
Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87686F (14 March 2013); doi: 10.1117/12.2021162
Show Author Affiliations
S. Bhuvaneswari, Pondicherry Univ. (India)
R. Vignashwaran, Amrita Univ. (India)


Published in SPIE Proceedings Vol. 8768:
International Conference on Graphic and Image Processing (ICGIP 2012)
Zeng Zhu, Editor(s)

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