Research concerning organization and coordination within multi-agent systems
continues to draw from a variety of architectures and methodologies. The work
presented in this paper combines techniques from game theory and multi-agent
systems to produce self-organizing, polymorphic, lightweight, embedded agents
for systems scheduling within a large-scale real-time systems environment.
Results show how this approach is used to experimentally produce optimum
real-time scheduling through the emergent behavior of thousands of agents.
These results are obtained using a SWARM simulation of systems scheduling
within a High Energy Physics experiment consisting of 2500 digital signal
processors.Comment: Fourth International Conference on Hybrid Intelligent Systems (HIS),
Kitakyushu, Japan, December, 200
