Neurocontrollers trained with rules extracted by a genetic assisted reinforcement learning system

@article{Zitar1995NeurocontrollersTW,
  title={Neurocontrollers trained with rules extracted by a genetic assisted reinforcement learning system},
  author={Raed Abu Zitar and Mohamad H. Hassoun},
  journal={IEEE transactions on neural networks},
  year={1995},
  volume={6 4},
  pages={859-79}
}
This paper proposes a novel system for rule extraction of temporal control problems and presents a new way of designing neurocontrollers. The system employs a hybrid genetic search and reinforcement learning strategy for extracting the rules. The learning strategy requires no supervision and no reference model. The extracted rules are weighted micro rules that operate on small neighborhoods of the admissable control space. A further refinement of the extracted rules is achieved by applying… CONTINUE READING
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