This paper describes a systems architecture for a hybrid Centralised/Swarm based multi-agent system. The issue of local goal assignment for agents is investigated through the use of a global agent which teaches the agents responses to given situations. We implement a test problem in the form of a Pursuit game, where the Multi-Agent system is a set of captor agents. The agents learn solutions to certain board positions from the global agent if they are unable to find a solution. The captor agents learn through the use of multi-layer perceptron neural networks. The global agent is able to solve board positions through the use of a Genetic Algorithm. The cooperation between agents and the results of the simulation are discussed here. .
@article{arxiv.0705.2307,
title = {A Study in a Hybrid Centralised-Swarm Agent Community},
author = {Bradley van Aardt and Tshilidzi Marwala},
journal= {arXiv preprint arXiv:0705.2307},
year = {2007}
}