Efficient Decentralized Policy Iteration using Approximate Linear Programming for Cooperative Multi-agent Markov Decision Processes

Approximate linear programming-based decentralized policy iteration algorithms for cooperative multi-agent Markov decision processes that provide computational savings over exact methods.