Effective decision making by self-evaluation in the multi-agent environment

Satoshi Kurihara; Kensuke Fukuda; Shihya Sato; Toshiharu Sugawara

doi:10.1007/11600930_63

Effective decision making by self-evaluation in the multi-agent environment

Satoshi Kurihara, Kensuke Fukuda, Shihya Sato, Toshiharu Sugawara

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Generally, in multi-agent systems, there are close relations between behavior of each individual agent and the group of agents as a whole, so a certain information about the relative state of each agent in the group may be hided in each agent behavior. If this information can be extracted, each agent has the possibility to improve its state by seeing only its own behavior without seeing other agents' behaviors. In this paper, we focus on "power-law" which is interesting character seen in the behavior of each node of various kinds of networks as one of such information. Up to now, we have already found that power-law can be seen in the efficiently behaving agents in Minority Game which is the competitive multi-agent simulation environment. So, in this paper we have verified whether it is possible for each agent in the game to improve its state by seeing only its own behavior, and confirmed that the performance gain was actually possible.

Original language	English
Title of host publication	Internet and Network Economics - First International Workshop, WINE 2005, Proceedings
Pages	631-640
Number of pages	10
DOIs	https://doi.org/10.1007/11600930_63
Publication status	Published - 2005 Dec 1
Externally published	Yes
Event	1st International Workshop on Internet and Network Economics, WINE 2005 - Hong Kong, China Duration: 2005 Dec 15 → 2005 Dec 17

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3828 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	1st International Workshop on Internet and Network Economics, WINE 2005
Country/Territory	China
City	Hong Kong
Period	05/12/15 → 05/12/17

Keywords

Indirect coordination
Minority game
Power law

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/11600930_63

Cite this

Kurihara, S., Fukuda, K., Sato, S., & Sugawara, T. (2005). Effective decision making by self-evaluation in the multi-agent environment. In Internet and Network Economics - First International Workshop, WINE 2005, Proceedings (pp. 631-640). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3828 LNCS). https://doi.org/10.1007/11600930_63

Effective decision making by self-evaluation in the multi-agent environment. / Kurihara, Satoshi; Fukuda, Kensuke; Sato, Shihya et al.
Internet and Network Economics - First International Workshop, WINE 2005, Proceedings. 2005. p. 631-640 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3828 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kurihara, S, Fukuda, K, Sato, S & Sugawara, T 2005, Effective decision making by self-evaluation in the multi-agent environment. in Internet and Network Economics - First International Workshop, WINE 2005, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3828 LNCS, pp. 631-640, 1st International Workshop on Internet and Network Economics, WINE 2005, Hong Kong, China, 05/12/15. https://doi.org/10.1007/11600930_63

Kurihara S, Fukuda K, Sato S, Sugawara T. Effective decision making by self-evaluation in the multi-agent environment. In Internet and Network Economics - First International Workshop, WINE 2005, Proceedings. 2005. p. 631-640. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11600930_63

Kurihara, Satoshi ; Fukuda, Kensuke ; Sato, Shihya et al. / Effective decision making by self-evaluation in the multi-agent environment. Internet and Network Economics - First International Workshop, WINE 2005, Proceedings. 2005. pp. 631-640 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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AB - Generally, in multi-agent systems, there are close relations between behavior of each individual agent and the group of agents as a whole, so a certain information about the relative state of each agent in the group may be hided in each agent behavior. If this information can be extracted, each agent has the possibility to improve its state by seeing only its own behavior without seeing other agents' behaviors. In this paper, we focus on "power-law" which is interesting character seen in the behavior of each node of various kinds of networks as one of such information. Up to now, we have already found that power-law can be seen in the efficiently behaving agents in Minority Game which is the competitive multi-agent simulation environment. So, in this paper we have verified whether it is possible for each agent in the game to improve its state by seeing only its own behavior, and confirmed that the performance gain was actually possible.

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Effective decision making by self-evaluation in the multi-agent environment

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