Salhi, A and T�reyen (2010) A Game Theory-Based Multi-Agent System for Expensive Optimisation Problems. In: Computational Intelligence in Optimization Applications and Implementations. Adaptation, Learning and Optimization . Springer Verlag, pp. 211-232. ISBN 9783642127748. Official URL: http://dx.doi.org/10.1007/978-3-642-12775-5_9
Salhi, A and T�reyen (2010) A Game Theory-Based Multi-Agent System for Expensive Optimisation Problems. In: Computational Intelligence in Optimization Applications and Implementations. Adaptation, Learning and Optimization . Springer Verlag, pp. 211-232. ISBN 9783642127748. Official URL: http://dx.doi.org/10.1007/978-3-642-12775-5_9
Salhi, A and T�reyen (2010) A Game Theory-Based Multi-Agent System for Expensive Optimisation Problems. In: Computational Intelligence in Optimization Applications and Implementations. Adaptation, Learning and Optimization . Springer Verlag, pp. 211-232. ISBN 9783642127748. Official URL: http://dx.doi.org/10.1007/978-3-642-12775-5_9
Abstract
This paper is concerned with the development of a novel approach to solve expensive optimisation problems. The approach relies on game theory and a multi-agent framework in which a number of existing algorithms, cast as agents, are deployed with the aim to solve the problem in hand as efficiently as possible. The key factor for the success of this approach is a dynamic resource allocation biased toward promising algorithms on the given problem. This is achieved by allowing the agents to play a cooperative-competitive game the outcomes of which will be used to decide which algorithms, if any, will drop out of the list of solver-agents and which will remain in use. A successful implementation of this framework will result in the most suited algorithm(s) for the given problem being predominantly used on the available computing platform. In other words it guarantees the best use of the resources both algorithms and hardware with the by-product being the best approximate solution for the problem given the available resources. GTMAS is tested on a standard collection of TSP problems. The results are included.
Item Type: | Book Section |
---|---|
Subjects: | Q Science > QA Mathematics |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Mathematics, Statistics and Actuarial Science, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 09 Jan 2012 13:34 |
Last Modified: | 25 Oct 2024 00:09 |
URI: | http://repository.essex.ac.uk/id/eprint/1821 |