Genetic learning of dynamic scheduling within a simulated environment

This paper proposes a learning mode for dynamic scheduling. A simulation environment having intelligent objects is described. Intelligent objects make decisions. A method is described in which intelligent objects can learn during the course of a simulation. The learning method is modeled after classifier systems using a Genetic Algorithm. Inference uses a bidding system. This study shows that intelligent objects can learn to perform within such an environment.