Multiagent coalition formation for distributed, adaptive resource allocation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a distributed, adaptive resource allocation approach for multiagent systems called ARAMS. ARAMS allows a collection of agents to adaptively allocate CPU resource among themselves to handle dynamic events encountered in a noisy and uncertain environment in real-time manner. Each event encountered may incur a CPU shortage crisis in an agent. ARAMS is aimed to reduce the occurrence and amount of shortage crises of each agent as well as the entire system as a whole. The underlying problem-solving strategy of ARAMS is the integration of a monitor-reactive cycle and a goal-directed coalition formation model. The monitor-reactive cycle requires the agent to monitor the crisis and attempt to fix it on its own. The goal-directed coalition formation allows the agent to ask for help from other agents rationally once it has the resources to do so. Agents also learn how to form better coalitions faster from their past experience. We conducted a series of experiments and the experimental results show that our approach to CPU resource allocation is able to learn and adapt coherently, reacting to and planning for CPU shortages.

Original languageEnglish (US)
Title of host publicationProceedings of the International Conference on Artificial Intelligence, IC-AI'04
EditorsH.R. Arabnia
Pages372-378
Number of pages7
StatePublished - 2004
EventProceedings of the International Conference on Artificial Intelligence, IC-AI'04 - Las Vegas, NV, United States
Duration: Jun 21 2004Jun 24 2004

Publication series

NameProceedings of the International Conference on Artificial Intelligence, IC-AI'04
Volume1

Conference

ConferenceProceedings of the International Conference on Artificial Intelligence, IC-AI'04
CountryUnited States
CityLas Vegas, NV
Period6/21/046/24/04

ASJC Scopus subject areas

  • Artificial Intelligence

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  • Cite this

    Soh, L. K., & Li, X. (2004). Multiagent coalition formation for distributed, adaptive resource allocation. In H. R. Arabnia (Ed.), Proceedings of the International Conference on Artificial Intelligence, IC-AI'04 (pp. 372-378). (Proceedings of the International Conference on Artificial Intelligence, IC-AI'04; Vol. 1).