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Self-organisation in an agent network via multiagent Q-learning

Citation

Ye, D and Zhang, M and Bai, Q and Ito, T, Self-organisation in an agent network via multiagent Q-learning, Proceedings of the 11th International Workshop on Knowledge Management and Acquisition for Smart Systems and Services (PKAW 2010), 20 August - 3 September 2010, Daegue, Korea, pp. 14-26. ISBN 978-3-642-15036-4 (2010) [Refereed Conference Paper]

Copyright Statement

Copyright 2010 Springer-Verlag Berlin Heidelberg

DOI: doi:10.1007/978-3-642-15037-1_2

Abstract

In this paper, a decentralised self-organisation mechanism in an agent network is proposed. The aim of this mechanism is to achieve efficient task allocation in the agent network via dynamically altering the structural relations among agents, i.e. changing the underlying network structure. The mechanism enables agents in the network to reason with whom to adapt relations and to learn how to adapt relations by using only local information. The local information is accumulated from agents' historical interactions with others. The proposed mechanism is evaluated through a comparison with a centralised allocation method and the K-Adapt method. Experimental results demonstrate the decent performance of the proposed mechanism in terms of several evaluation criteria.

Item Details

Item Type:Refereed Conference Paper
Keywords:wireless sensor network, communication cost, task allocation, small world network, agent network
Research Division:Information and Computing Sciences
Research Group:Artificial intelligence
Research Field:Intelligent robotics
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Application software packages
UTAS Author:Bai, Q (Dr Quan Bai)
ID Code:140719
Year Published:2010
Deposited By:Information and Communication Technology
Deposited On:2020-09-02
Last Modified:2020-11-09
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