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This paper introduces semi-decentralized POMDPs (SDec-POMDPs) as a framework for multi-agent control under communication uncertainty, where agents have probabilistic control over their action and observation history. They unify decentralized and multiagent POMDPs by introducing semi-Markov communication. The authors also present RS-SDA*, an exact algorithm for generating optimal policies for SDec-POMDPs, and evaluate it on standard benchmarks and a maritime medical evacuation scenario.
Semi-decentralized POMDPs offer a unifying framework that subsumes decentralized and multiagent POMDPs, enabling a more nuanced approach to communication constraints in multi-agent systems.
We introduce an expressive framework and algorithms for the semi-decentralized control of cooperative agents in environments with communication uncertainty. Whereas semi-Markov control admits a distribution over time for agent actions, semi-Markov communication, or what we refer to as semi-decentralization, gives a distribution over time for what actions and observations agents can store in their histories. We extend semi-decentralization to the partially observable Markov decision process (POMDP). The resulting SDec-POMDP unifies decentralized and multiagent POMDPs and several existing explicit communication mechanisms. We present recursive small-step semi-decentralized A* (RS-SDA*), an exact algorithm for generating optimal SDec-POMDP policies. RS-SDA* is evaluated on semi-decentralized versions of several standard benchmarks and a maritime medical evacuation scenario. This paper provides a well-defined theoretical foundation for exploring many classes of multiagent communication problems through the lens of semi-decentralization.
