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Self-Organising Agent Organisations

Self-Organising Agent Organisations
Self-Organising Agent Organisations
Self-organising multi-agent systems provide a suitable paradigm for developing autonomic computing systems that manage themselves. Towards this goal, we demonstrate a robust, decentralised approach for structural adaptation in explicitly modelled problem solving agent organisations. Based on self-organisation principles, our method enables the agents to modify their structural relations to achieve a better allocation of tasks in a simulated task-solving environment. The agents reason on when and how to adapt using only their history of interactions as guidance. We empirically show that, in both closed and dynamic organisations, the performance of organisations using our method is close to that of an upper bound centralised allocation method and considerably better than a random adaptation method.
Autonomic computing, Self-Organisation, Organisations, Structural Adaptation
797-804
Kota, Ramachandra
a2b6c536-fa54-4d9e-8f3d-c3fb66f79b86
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Jennings, Nicholas R
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Kota, Ramachandra
a2b6c536-fa54-4d9e-8f3d-c3fb66f79b86
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Jennings, Nicholas R
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Kota, Ramachandra, Gibbins, Nicholas and Jennings, Nicholas R (2009) Self-Organising Agent Organisations. The 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS '09), Budapest, Hungary. 10 - 15 May 2009. pp. 797-804 .

Record type: Conference or Workshop Item (Paper)

Abstract

Self-organising multi-agent systems provide a suitable paradigm for developing autonomic computing systems that manage themselves. Towards this goal, we demonstrate a robust, decentralised approach for structural adaptation in explicitly modelled problem solving agent organisations. Based on self-organisation principles, our method enables the agents to modify their structural relations to achieve a better allocation of tasks in a simulated task-solving environment. The agents reason on when and how to adapt using only their history of interactions as guidance. We empirically show that, in both closed and dynamic organisations, the performance of organisations using our method is close to that of an upper bound centralised allocation method and considerably better than a random adaptation method.

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More information

Published date: May 2009
Additional Information: Event Dates: 10-15 May, 2009
Venue - Dates: The 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS '09), Budapest, Hungary, 2009-05-10 - 2009-05-15
Keywords: Autonomic computing, Self-Organisation, Organisations, Structural Adaptation
Organisations: Web & Internet Science, Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 267071
URI: http://eprints.soton.ac.uk/id/eprint/267071
PURE UUID: ff0d57af-821b-4477-bd35-d355aad3bafb
ORCID for Nicholas Gibbins: ORCID iD orcid.org/0000-0002-6140-9956

Catalogue record

Date deposited: 30 Jan 2009 16:02
Last modified: 15 Mar 2024 02:59

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Contributors

Author: Ramachandra Kota
Author: Nicholas Gibbins ORCID iD
Author: Nicholas R Jennings

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