Covering Number for Efficient Heuristic-based POMDP Planning
Proceedings of the 31st International Conference on Machine Learning, PMLR 32(1):28-36, 2014.
The difficulty of POMDP planning depends on the size of the search space involved. Heuristics are often used to reduce the search space size and improve computational efficiency; however, there are few theoretical bounds on their effectiveness. In this paper, we use the covering number to characterize the size of the search space reachable under heuristics and connect the complexity of POMDP planning to the effectiveness of heuristics. With insights from the theoretical analysis, we have developed a practical POMDP algorithm, Packing-Guided Value Iteration (PGVI). Empirically, PGVI is competitive with the state-of-the-art point-based POMDP algorithms on 65 small benchmark problems and outperforms them on 4 larger problems.