エージェントの組織による実時間連続問題解決

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Recently developed production system techniques have improved the performance of problem solving several times over. However, these techniques cannot be solutions for real-time continuous problem solving systems, where meaningful results are required within a predefined time limit. To satisfy real-time constraints, this paper proposes an organizational approach, where problems are solved not by a single production system, but by an organization of distributed production system agents. To explore the effectiveness of the organizational approach, we are studying the adaptive load balancing problem in which multiple problem solving organizations share a collection of processor resources. Problem solving requests arrive at the organization continuously, at variable rates. Meaningful results are required within a (possibly changing) time limit. Since the organization shares computing resources with other organizations, it does not suffice to decompose to maximal parallesism -the collective must adapt itself to take advantage of resources it can, but it must also adaptively free up resources for others while continuing to operate. Organizational self-design is then performed to equalize response times. For this purpose, we introduce new reorganization primitives, composition and decomposition, which change the number of agents in organization. Various simulation results prove the effectiveness of composition/decomposition techniques for building adaptive real-time production systems.
社団法人人工知能学会の論文
1992-03-01

エージェントの組織による実時間連続問題解決

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