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A variety of alternate training strategies for implementing the Dual Heuristic Programming (DHP) method of approximate dynamic programming in the neuro-control context are explored. The DHP method of controller training has been successfully demonstrated by a number of authors on a variety of control problems in recent years, but no unified view of the implementation details of the method has yet emerged. A number of options are here described for sequencing the training of the Controller and Critic networks in DHP implementations. Results are given about their relative efficiency and the quality of the resulting controllers for two benchmark control problems.


Proceedings of the International Joint Conference on Neural Networks

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