Highly Influenced

@inproceedings{Theocharous2010CompressingPU, title={Compressing POMDPs Using Locality Preserving Non-Negative Matrix Factorization}, author={Georgios Theocharous and Sridhar Mahadevan}, booktitle={AAAI}, year={2010} }

- Published 2010 in AAAI

Partially Observable Markov Decision Processes (POMDPs) are a well-established and rigorous framework for sequential decision-making under uncertainty. POMDPs are well-known to be intractable to solve exactly, and there has been significant work on finding tractable approximation methods. One well-studied approach is to find a compression of the original… CONTINUE READING

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