Asynchronous Vector Iteration in Multi-objective Markov Decision Processes.

This paper presents new algorithms to solve Multi-Objective Markov Decision Processes (MOMDPs). Namely, we present Multi-objective Dynamic Programming variants of Value Iteration such that the values for every state are updated in some heuristic order. The performance of these algorithms is evaluated applying them to benchmark problems with two and three objectives.