COOPERATIVE LEARNING OF BDI ELEVATOR AGENTS

Yuya Takata, Yuki Mikura, Hiroaki Ueda, Kenichi Takahashi

2010

Abstract

We propose a framework of cooperative learning of BDI agents. Our framework uses some kinds of agents, including a task management agent (TMA) and rational agents. TMA is designed as a learning agent. It manages assignment of tasks to rational agents. When a task is created, TMA evaluates the most useful strategy on the basis of reinforcement learning. Rational agents also evaluate the value that the task is assigned to them according to the strategy, and they give the value as their intention to TMA. Then, TMA optimally assigns the task to a rational agent by using both the value and the rough strategies, and the rational agent processes the task. In this article, we apply the proposed method to an elevator group control problem. Experiment results show that the proposed method finds better task assignment than the methods without cooperative learning.

References

  1. Braubach, L. and Pokahr, A. (accessed 11 August, 2009). Jadex BDI agent system - overview. http://vsis-www.informatik.unihamburg.de/projects/jadex/.
  2. Doniec, A., Espié, S., Mandiau, R., and Piechowiak, S. (2006). Non-normative behaviour in multi-agent system: Some experiments in traffic simulation. In Proceedings of IAT2006, pages 30-36.
  3. Excelente-Toledo, C. B. and Jennings, N. R. (2003). Learning when and how to coordinate. Web Intelligence and Agent Systems, IOS Press, 1(3-4):203-218.
  4. Ikeda, K., Suzuki, H., Kita, H., and Markin, S. (2008). Exemplar-based control of multi-car elevators and its multi-objective optimization using genetic algorithm. In The 23rd International Technical Conference on Circuits/Systems, Computers and Communications, pages 701-704.
  5. Katagiri, H., Hirakawa, K., and Hu, J. (2000). Genetic network programming - application to intelligent agents -. In Proceedings of SMC2000, pages 3829-3834.
  6. Rao, A. S. and Georgeff, M. P. (1991). Modeling rational agents within a BDI-architecture. In Proceedings of KR'91, pages 473-484.
  7. Sutton, R. S. and Barto, A. G. (1998). Reinforcement Learning. The MIT Press.
  8. The IEICE Engineering Sciences Society, Concurrent System Technology (accessed 11 August, 2009). CST solution competition 2008. http://www.ieice.org/ cst/compe08/. (in Japanese).
  9. The RoboCup Federation (accessed 11 August, 2009). http://www.robocup.org/.
  10. Valdivielso, A., Miyamoto, T., and Kumagai, S. (2008). Multi-car elevator group control: Schedule completion time optimization algorithm with synchronized schedule direction and service zone coverage oriented parking strategies. In The 23rd International Technical Conference on Circuits/Systems, Computers and Communications, pages 689 - 692.
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Paper Citation


in Harvard Style

Takata Y., Mikura Y., Ueda H. and Takahashi K. (2010). COOPERATIVE LEARNING OF BDI ELEVATOR AGENTS . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-674-022-1, pages 172-177. DOI: 10.5220/0002717201720177


in Bibtex Style

@conference{icaart10,
author={Yuya Takata and Yuki Mikura and Hiroaki Ueda and Kenichi Takahashi},
title={COOPERATIVE LEARNING OF BDI ELEVATOR AGENTS},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2010},
pages={172-177},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002717201720177},
isbn={978-989-674-022-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - COOPERATIVE LEARNING OF BDI ELEVATOR AGENTS
SN - 978-989-674-022-1
AU - Takata Y.
AU - Mikura Y.
AU - Ueda H.
AU - Takahashi K.
PY - 2010
SP - 172
EP - 177
DO - 10.5220/0002717201720177