Communicative Multiagent Team Decision Problems (COM-MTDPs)
David V. Pynadath and Milind Tambe
Despite the significant progress in multiagent teamwork, existing research does not address the optimality of its prescriptions nor the complexity of the teamwork problem. Without a characterization of the optimality-complexity tradeoffs, it is impossible to determine whether the assumptions and approximations made by a particular theory gain enough efficiency to justify the losses in overall performance. To provide a tool for use by multiagent researchers in evaluating this tradeoff, we present a unified framework, the COMmunicative Multiagent Team Decision Problem (COM-MTDP). The COM-MTDP model combines and extends existing multiagent theories, such as decentralized partially observable Markov decision processes and economic team theory. In addition to their generality of representation, COM-MTDPs also support the analysis of both the optimality of team performance and the computational complexity of the agents' decision problem. In analyzing complexity, we present a breakdown of the computational complexity of constructing optimal teams under various classes of problem domains, along the dimensions of observability and communication cost. In analyzing optimality, we exploit the COM-MTDP's ability to encode existing teamwork theories and models to encode two instantiations of joint intentions theory taken from the literature (Jennings 1995,Tambe 1997). Furthermore, the COM-MTDP model provides a basis for the development of novel coordination algorithms. We derive a domain-independent criterion for optimal communication and provide a comparative analysis of the two joint intentions instantiations with respect to this optimal policy. We have implemented a reusable, domain-independent software package based COM-MTDPs to analyze teamwork coordination strategies, and we demonstrate its use by encoding and evaluating the two joint intentions strategies within an example domain.
A complete proof of Theorem 7 is available in both PS and PDF.
We have implemented the COM-MTDP model as a Python class, allowing one to instantiate a particular problem domain as an object of this class. The following class files support the setting up of the various components of an COM-MTDP:
The following class file supports the construction of policies of behavior: The following class file provides the code used to set up and evaluate the example domain from the article: Documentation is (or will soon be) available. If you have any comments, questions, or improvements, please let us know. Thanks and enjoy!