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.

arXiv comment15 pages

Cited by in corpus (2)

• Optimistic Policy Iteration for MDPs with Acyclic Transient State Structure
• On the Convergence of Reinforcement Learning with Monte Carlo Exploring Starts