Feb 20, 2013 · In this paper, we summarize results regarding the complexity of solving MDPs and the running time of MDP solution algorithms.

A Markov decision problem (MDP) is a Markov de cision process together with a performance criterion. The performance criterion enables us to assign a total cost ...

The Markov decision problem provides a mathematical framework for dynamic programming, stochastic control, and reinforcement learning. In this thesis, we study ...

In this thesis, we study the complexity of solving MDPs. In the first part of the thesis, we propose a class of stochastic primal-dual methods for solving MDPs.

We investigate the complexity of the classical problem of optimal policy computation in. Markov decision processes. All three variants of the problem (finite ...

We investigate the complexity of the classical problem of optimal policy computation in. Markov decision processes. All three variants of the problem ...

In this paper, we summarize results regarding the complexity of solving MDPs and the running time of MDP solution algorithms. We argue that, although MDPs can ...

In this paper, we summarize results regarding the complexity of solving MDPs and the running time of MDP solution algorithms. We argue that, although MDPs can ...

The complexity of algorithms for solving Markov Decision Processes (MDPs) with finite state and action spaces has seen renewed interest in recent years. New.

All three variants of the classical problem of optimal policy computation in Markov decision processes, finite horizon, infinite horizon discounted, ...