Randall Beer

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This paper explores the use of dynamical neural networks to control autonomous agents in tasks requiring reactive, sequential, and learning behavior. We use a genetic algorithm to evolve networks that can integrate these different types of behavior in a smooth, continuous manner. We apply this approach to three different task domains: landmark recognition(More)
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