2005/04/29 by Derek Messie, Messie, Derek, Jae C. Oh +1
Computer Science · Decision Sciences · Engineering · #Distributed and Parallel Computing Systems #Scheduling and Optimization Algorithms #Simulation Techniques and Applications #cs.AI #cs.MA
paper · pdf · doi:10.48550/arxiv.cs/0504108
Fourth International Conference on Hybrid Intelligent Systems (HIS), Kitakyushu, Japan, December, 2004
arxiv created 2005/04/29 · arxiv updated 2009/12/01
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.