Application of confidence level based on agents experience to improve internal model

International Journal of Innovative Computing, Information and Control

Volumn 4, Issue 5, 2008, Pages 1161-1168

  Shibata, Junko ^a   Okuhara, Koji ^b   Shode, Shogo ^a   Ishii, Hiroaki ^b  

^a KOBE GAKUIN UNIVERSITY   (Japan)

^b OSAKA UNIVERSITY   (Japan)

Author keywords

Confidence level; Multi agent system; Sugarscape model; Temperature parameter of internal model

Indexed keywords

EID: 48249087264     PISSN: 13494198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (16)

1. A. Namatame, S. Iwanaga and H. Sato, Self-organization by micro-macro loop and its evaluation, Journal of the Institute of System, Control and Information Engineers, vol.46, no.9, pp.561-568, 2002.
2. T. Sato and T. Hashimoto, Dynamic social simulation with multi-agent having internal dynamics, The 18th Annual Conference of the Japanese Society for Artificial Intelligence, 2H2-03, 2004.
3. A. Namatame, Multi-agent Systems and Complex Systems, Morikita, 1998 (in Japanese).
4. N. Nakano, An agent-based approach to simulations of global influence with random effect, International Journal of Innovative Computing, Information and Control, vol.2, no.5, pp.1153-1163, 2006.
5. J. M. Epstein and R. Axtell, Growing artificial societies, Brookings Institution Press, 1996.
6. F. Flentge, D. Polani and T. Uthmann, Modelling the emergence of possession norms using memes, Journal of Artificial Societies and Social Simulation, vol.4, no.4, 2001.
7. W. Yun and H. Kanoh, Evolutionary design of rule changing axtificial society using genetic algorithms, Transactions of the Japanese Society of for Artificial Intelligence, vol.20, pp.318-325, 2005.
8. S. Kurahashi and T. Terano, Analyzing norm emergence in communal sharing via agent-based simulation, IEICE, J84-D-1, no.8, pp.1160-1168, 2001.
9. K. Okuhara, J. Shibata and H. Ishii, Adaptive worker's arrangement and workload control for project management by genetic algorithm, International Journal of Innovative Computing, Information and Control, vol.3, no.1, pp.175-188, 2007.
10. R. S. Sutton and A. Barto, Reinforcement learning, A Bradford Book, The MIT Press, 1998.
11. J. Shibata, K. Okuhara and H. Ishii, The study of social interaction using agent-based simulations, Proc. of the 11th Asia Pacific Management Conference, pp.2B-3, 2005.
12. J. Shibata, K. Okuhara, S. Shiode and H. Ishii, The study of the coarse graining of environmental conditions which suited to sugarscape model, Proc. of the 11th Annual International Conference on Industrial Engineering - Theory, Applications and Practice, pp.982-986, 2006.
13. J. Shibata, K. Okuhara, H. Ishii and S. Shiode, Artificial society using sugarscape model which consists of agents with Q-learning, IEICE, J90-A, no.1, pp.35-43, 2007.
14. J. Shibata, K. Okuhara, S. Saito, S. Shiode and H. Ishii, Analysis of time series derived from sugarscape model which is composed of trading agent, Proc. of the 12th Asia Pacific Management Conference, pp.1307-1310, 2006.
15. J. Shibata, Acquirement of the movement rule in agent system with pheromone communication, Kobe Gakuin Economic Papers, vol.38, no.12, pp.63-71, 2006.
16. C. J. C. H. Watkins and P. Dayan, Technical note Q-learning, Machine Learning, vol.8, pp.279-292, 1992.