Combination of acceleration procedures for solving stochastic shortest-path Markov decision processes

In this paper we propose the combination of accelerated variants of value iteration with improved prioritized sweeping for the solution of stochastic shortest path Markov decision processes. For the fastest solution, asynchronous updates, prioritization and prioritized sweeping have been tested. A topological reordering algorithm was also compared with a static reordering algorithm. Experimental results obtained on a finite state and action-space stochastic shortest path problem are presented.