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Decentralised Approaches for Self-Adaptation in Agent Organisations

Decentralised Approaches for Self-Adaptation in Agent Organisations
Decentralised Approaches for Self-Adaptation in 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 autonomous agents to modify their structural relations to achieve a better allocation of tasks in a simulated task-solving environment. Specifically, the agents reason about when and how to adapt using only their history of interactions as guidance. We empirically show that, in a wide range of closed, open, static and dynamic scenarios, the performance of organisations using our method is close (70-90%) to that of an idealised centralised allocation method and is considerably better (10-60%) than the current state of the art decentralised approaches.
Autonomic computing, Self-Organisation, Adaptation, Organisation Structure, Agent Organisation
1-28
Kota, Ramachandra
a2b6c536-fa54-4d9e-8f3d-c3fb66f79b86
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30
Kota, Ramachandra
a2b6c536-fa54-4d9e-8f3d-c3fb66f79b86
Gibbins, Nicholas
98efd447-4aa7-411c-86d1-955a612eceac
Jennings, Nick
ab3d94cc-247c-4545-9d1e-65873d6cdb30

Kota, Ramachandra, Gibbins, Nicholas and Jennings, Nick (2012) Decentralised Approaches for Self-Adaptation in Agent Organisations. ACM Transactions on Autonomous and Adaptive Systems, 7 (1), 1-28.

Record type: Article

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 autonomous agents to modify their structural relations to achieve a better allocation of tasks in a simulated task-solving environment. Specifically, the agents reason about when and how to adapt using only their history of interactions as guidance. We empirically show that, in a wide range of closed, open, static and dynamic scenarios, the performance of organisations using our method is close (70-90%) to that of an idealised centralised allocation method and is considerably better (10-60%) than the current state of the art decentralised approaches.

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More information

Published date: 2012
Keywords: Autonomic computing, Self-Organisation, Adaptation, Organisation Structure, Agent Organisation
Organisations: Web & Internet Science, Agents, Interactions & Complexity

Identifiers

Local EPrints ID: 271602
URI: https://eprints.soton.ac.uk/id/eprint/271602
PURE UUID: 11c18e0e-5f73-4100-bdec-bc90dde0d679
ORCID for Nicholas Gibbins: ORCID iD orcid.org/0000-0002-6140-9956

Catalogue record

Date deposited: 28 Sep 2010 14:21
Last modified: 06 Jun 2018 12:55

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Contributors

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

University divisions

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