On the convergence of optimistic policy iteration for stochastic shortest path problem

Abstract:In this paper, we prove some convergence results of a special case of optimistic policy iteration algorithm for stochastic shortest path problem. We consider both Monte Carlo and $TD(\lambda)$ methods for the policy evaluation step under the condition that the termination state will eventually be reached almost surely.

Machine Learning (cs.LG); Machine Learning (stat.ML)

arXiv:1808.08763 [cs.LG]

(or arXiv:1808.08763v3 [cs.LG] for this version)

https://doi.org/10.48550/arXiv.1808.08763 Focus to learn more arXiv-issued DOI via DataCite

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