Artificial Intelligence, Multiagent Systems
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.
Messie, Derek and Oh, Jae C., "Cooperative Game Theory within Multi-Agent Systems for Systems Scheduling" (2004). Electrical Engineering and Computer Science. Paper 44.
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