An Organizational Approach to Adaptive Production Systems

Toru Ishida, Makoto Yokoo, Les Gasser

Recently-developed techniques have improved the performance of production systems several times over. However, these techniques are not yet adequate for continuous problem solving in a dynamically changing environment. To achieve adaptive real-time performance in such environments, we use an organization of distributed production system agents, rather than a single monolithic production system, to solve problems. Organization self-design is performed to satisfy real-time constraints and to adapt to changing resource requirements. When overloaded, individual agents decompose themselves to increase parallelism, and when the load lightens the agents compose with each other to free hardware resources. In addition to increased performance, generalizations of our composition/decomposition approach provide several new directions for organization self-design, a pressing concern in Distributed AI.

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