Focused Dynamic Programming: Extensive Comparative Results
CARNEGIE-MELLON UNIV PITTSBURGH PA ROBOTICS INST
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We present a heuristic-based propagation algorithm for solving restricted Markov decision processes MDPs. Our approach, which combines ideas from deterministic search and recent dynamic programming methods, focuses computation towards promising areas of the state space. It is thus able to significantly reduce the amount of processing required in producing a solution. We present a number of results comparing our approach to existing algorithms on a robotic path planning domain.
- Statistics and Probability
- Operations Research