Towards Addressing Model Uncertainty: Robust Execution-time Coordination for Teamwork (Short Paper)


Jun-young Kwak, Rong Yang, Zhengyu Yin, Matthew E. Taylor, and Milind Tambe. 2011. “Towards Addressing Model Uncertainty: Robust Execution-time Coordination for Teamwork (Short Paper) .” In International Conference on Intelligent Agent Technology (short paper).


Despite their worst-case NEXP-complete planning complexity, DEC-POMDPs remain a popular framework for multiagent teamwork. This paper introduces effective teamwork under model uncertainty (i.e., potentially inaccurate transition and observation functions) as a novel challenge for DEC-POMDPs and presents MODERN, the first executioncentric framework for DEC-POMDPs explicitly motivated by addressing such model uncertainty. MODERN’s shift of coordination reasoning from planning-time to execution-time avoids the high cost of computing optimal plans whose promised quality may not be realized in practice. There are three key ideas in MODERN: (i) it maintains an exponentially smaller model of other agents’ beliefs and actions than in previous work and then further reduces the computationtime and space expense of this model via bounded pruning; (ii) it reduces execution-time computation by exploiting BDI theories of teamwork, and limits communication to key trigger points; and (iii) it limits its decision-theoretic reasoning about communication to trigger points and uses a systematic markup to encourage extra communication at these points — thus reducing uncertainty among team members at trigger points. We empirically show that MODERN is substantially faster than existing DEC-POMDP execution-centric methods while achieving significantly higher reward.
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