Transition-independent decentralized markov decision processes

Raphen Becker, Shlomo Zilberstein, Victor Lesser, Claudia V. Goldman
2003 Proceedings of the second international joint conference on Autonomous agents and multiagent systems - AAMAS '03  
There has been substantial progress with formal models for sequential decision making by individual agents using the Markov decision process (MDP). However, similar treatment of multi-agent systems is lacking. A recent complexity result, showing that solving decentralized MDPs is NEXPhard, provides a partial explanation. To overcome this complexity barrier, we identify a general class of transitionindependent decentralized MDPs that is widely applicable. The class consists of independent
more » ... independent collaborating agents that are tied together through a global reward function that depends upon both of their histories. We present a novel algorithm for solving this class of problems and examine its properties. The result is the first effective technique to solve optimally a class of decentralized MDPs. This lays the foundation for further work in this area on both exact and approximate solutions.
doi:10.1145/860581.860583 fatcat:qpd3fwwcv5c3fjtsvkm6ujtdoa