Design support mechanism of learning agent on repository-based agent framework

Syo Itazuro, Takahiro Uchiya, Ichi Takumi, Tetsuo Kinoshita

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Agent-oriented computing is a technique for generating an agent that operates autonomously according to behavior knowledge. Moreover, an agent can have a characteristic called "Learning" skill. More efficient operation of an agent can be expected by realizing "Learning" skill. In this research, our aim is to support an agent designer who designs and develops an agent equipped with "Learning" skill. We propose a design support mechanism of a learning agent on a repository-based agent framework called the DASH framework. The proposed mechanism enables an agent designer to design and implement the learning agent without great expertise, thereby reducing the designer's burden. Herein, we explain the DASH framework, Q-Learning, and the proposed design support mechanism. Moreover, we demonstrate the effectiveness of the proposed method using some experiments.

Original languageEnglish
Title of host publicationProceedings of the 11th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2012
Pages300-304
Number of pages5
DOIs
Publication statusPublished - 2012 Nov 15
Event11th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2012 - Kyoto, Japan
Duration: 2012 Aug 222012 Aug 24

Publication series

NameProceedings of the 11th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2012

Other

Other11th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2012
Country/TerritoryJapan
CityKyoto
Period12/8/2212/8/24

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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