Characteristic Analysis of Agents in Adaptive Consensus Formation Models

Oumi, Hiroaki; Mitamura, Tamotsu; Kurihara, Masahito; Oohori, Takafumi; Yoshikawa, Takeshi

doi:10.1007/3-540-32391-0_135

Cited by 3 publications

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“…In addition, Omura designed the social adaptive agent which tried to adapt the group (Omura et al 2008), but did not find any conditions that enable the agents to lead the collective adaptation. As other related works, Oumi et al (2006) proposed an agent model that could reach consensus and analyzed characteristics of agents in the consensus situation. However, this model did not deal with a leader required to derive the collective adaptive situation and the effect of the leader, which have attracted much attention in the area of group dynamics (Cartwright and Zander 1968) and organizational behavior (Hersey et al 1977), in which intensive researches on the theory of a leader have been done.…”

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confidence: 99%

Modeling collective adaptive agent design and its analysis in Barnga game

Ushida

Hattori

Takdama

2010

J Econ Interact Coord

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This paper explores the collective adaptive agent that adapts to a group in contrast with the individual adaptive agent that adapts to a single user. For this purpose, this paper starts by defining the collective adaptive situation through an analysis of the subject experiments in the playing card game, Barnga, and investigates the factors that lead the group to the collective adaptive situation. Intensive simulations using Barnga agents have revealed the following implications: (1) the leader who takes account of other players' opinions contributes to guide players to the collective adaptation situation, and (2) an appropriate role balance among players (i.e., the leader, the claiming and quiet players, which make the most and least number of corrections of the leader's decision) is required to derive the collective adaptive situation.

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confidence: 99%

Modeling collective adaptive agent design and its analysis in Barnga game

Ushida

Hattori

Takdama

2010

J Econ Interact Coord

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Consensus formation models based on structural modeling

Mitamura¹,

Oohori²,

Kurihara

2008

2008 IEEE International Conference on Systems, Man and Cybernetics

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Simulation of consensus formation models based on Structural Modeling

Mitamura

Oohori

Kurihara

2010

2010 IEEE International Conference on Systems, Man and Cybernetics

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Abstract-Consensus formation models are mathematical models for obtaining potential candidates for a group when all group members pursue their individual preferences. In such models, the members often change their preferences based on the group's global preference which summarizes the overall individual preferences. Based on the theory of partially-filled reachability matrices, the Flexible Interpretive Structural Modeling (FISM) provides a method for developing structural models of complex systems and is expected to be applied to decision-making support systems. In this paper, we propose a method for simulating consensus formation in FISM and study its effectiveness through the experiments with several consensus strategies.

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Characteristic Analysis of Agents in Adaptive Consensus Formation Models

Cited by 3 publications

References 1 publication

Modeling collective adaptive agent design and its analysis in Barnga game

Modeling collective adaptive agent design and its analysis in Barnga game

Consensus formation models based on structural modeling

Simulation of consensus formation models based on Structural Modeling

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