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Solving POMDPs by Searching in Policy Space

arXiv 1301.7380 ↗First posted 30 Jan 2013cs.AIcited by 13

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Abstract (arXiv)

Most algorithms for solving POMDPs iteratively improve a value function that implicitly represents a policy and are said to search in value function space. This paper presents an approach to solving POMDPs that represents a policy explicitly as a finite-state controller and iteratively improves the controller by search in policy space. Two related algorithms illustrate this approach. The first is a policy iteration algorithm that can outperform value iteration in solving infinitehorizon POMDPs. It provides the foundation for a new heuristic search algorithm that promises further speedup by focusing computational effort on regions of the problem space that are reachable, or likely to be reached, from a start state.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Jan 2013.

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Citing papers per year: 2021: 4; 2022: 2; 2023: 1; 2024: 3; 2025: 2; 2026: 1.

13 papers.

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