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Coalition formation through motivation and trust

Coalition formation through motivation and trust
Coalition formation through motivation and trust
Cooperation is the fundamental underpinning of multi-agent systems, allowing agents to interact to achieve their goals. Where agents are self-interested, or potentially unreliable, there must be appropriate mechanisms to cope with the uncertainty that arises. In particular, agents must manage the risk associated with interacting with others who have different objectives, or who may fail to fulfil their commitments. Previous work has utilised the notions of motivation and trust in engendering successful cooperation between self-interested agents. Motivations provide a means for representing and reasoning about agents’ overall objectives, and trust offers a mechanism for modelling and reasoning about reliability, honesty, veracity and so forth. This paper extends that work to address some of its limitations. In particular, we introduce the concept of a clan: a group of agents who trust each other and have similar objectives. Clan members treat each other favourably when making private decisions about cooperation, in order to gain mutual benefit. We describe mechanisms for agents to form, maintain, and dissolve clans in accordance with their self-interested nature, along with giving details of how clan membership influences individual decision making. Finally, through some simulation experiments we illustrate the effectiveness of clan formation in addressing some of the inherent problems with cooperation among self-interested agents.
Cooperation, coalitions, clans, trust, motivation
17-24
Griffiths, N
71f8d918-d23e-4f7b-bf21-d893d18c3ba2
Luck, Michael
94f6044f-6353-4730-842a-0334318e6123
Griffiths, N
71f8d918-d23e-4f7b-bf21-d893d18c3ba2
Luck, Michael
94f6044f-6353-4730-842a-0334318e6123

Griffiths, N and Luck, Michael (2003) Coalition formation through motivation and trust. The Second International Joint Conference on Autonomous Agents and Multi-Agent Systems, Melbourne, Australia. pp. 17-24 .

Record type: Conference or Workshop Item (Paper)

Abstract

Cooperation is the fundamental underpinning of multi-agent systems, allowing agents to interact to achieve their goals. Where agents are self-interested, or potentially unreliable, there must be appropriate mechanisms to cope with the uncertainty that arises. In particular, agents must manage the risk associated with interacting with others who have different objectives, or who may fail to fulfil their commitments. Previous work has utilised the notions of motivation and trust in engendering successful cooperation between self-interested agents. Motivations provide a means for representing and reasoning about agents’ overall objectives, and trust offers a mechanism for modelling and reasoning about reliability, honesty, veracity and so forth. This paper extends that work to address some of its limitations. In particular, we introduce the concept of a clan: a group of agents who trust each other and have similar objectives. Clan members treat each other favourably when making private decisions about cooperation, in order to gain mutual benefit. We describe mechanisms for agents to form, maintain, and dissolve clans in accordance with their self-interested nature, along with giving details of how clan membership influences individual decision making. Finally, through some simulation experiments we illustrate the effectiveness of clan formation in addressing some of the inherent problems with cooperation among self-interested agents.

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More information

Published date: 2003
Additional Information: Event Dates: 2003
Venue - Dates: The Second International Joint Conference on Autonomous Agents and Multi-Agent Systems, Melbourne, Australia, 2003-01-01
Keywords: Cooperation, coalitions, clans, trust, motivation
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 257310
URI: http://eprints.soton.ac.uk/id/eprint/257310
PURE UUID: b86e1caa-cb3a-4f06-8bb4-d8f591340749

Catalogue record

Date deposited: 29 Nov 2003
Last modified: 14 Mar 2024 05:56

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Contributors

Author: N Griffiths
Author: Michael Luck

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