R. Cogill, M. Rotkowitz, B. Van Roy, and S. Lall
An Approximate Dynamic Programming Approach to Decentralized Control of Stochastic Systems
Lecture Notes in Control and Information Sciences vol. 329, Control of Uncertain Systems: Modelling, Approximation, and Design,
(A Workshop on the Occasion of Keith Glover's 60th Birthday), pp. 243-256, April 2006.


We consider the problem of computing decentralized control policies for stochastic systems with finite state and action spaces. Synthesis of optimal decentralized policies for such problems is known to be NP-hard [1]. Here we focus on methods for efficiently computing meaningful suboptimal decentralized control policies. The algorithms we present here are based on approximation of optimal Qfunctions. We show that the performance loss associated with choosing decentralized policies with respect to an approximate Q-function is related to the approximation error.