Type: Book Section
Csáji, Balázs Csanád and Monostori, László
Stochastic Reactive Production Scheduling by Multi-Agent Based Asynchronous Approximate Dynamic Programming.
Multi-Agent Systems and Applications IV (CEEMAS 2005).
Lecture Notes in Artificial Intelligence, 3690.
Springer, Germany, .
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The paper investigates a stochastic production scheduling
problem with unrelated parallel machines. A closed-loop scheduling technique is presented that on-line controls the production process. To achieve this, the scheduling problem is reformulated as a special Markov Decision Process. A near-optimal control policy of the resulted MDP is calculated in a homogeneous multi-agent system. Each agent applies a trial-based approximate dynamic programming method. Di®erent cooperation techniques to distribute the value function computation among the agents are described. Finally, some benchmark experimental results are shown.
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