@article {1510351,
	title = {The communicative multiagent team decision problem: Analyzing teamwork theories and models },
	journal = {Journal of AI Research (JAIR)},
	volume = {16},
	year = {2002},
	pages = {389-423},
	abstract = {Despite the signicant 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 tradeos, it is impossible to determine
whether the assumptions and approximations made by a particular theory gain enough
eciency to justify the losses in overall performance. To provide a tool for use by multiagent researchers in evaluating this tradeo, we present a unied 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{\textquoteright} 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{\textquoteright}s
ability to encode existing teamwork theories and models to encode two instantiations of
joint intentions theory taken from the literature. Furthermore, the COM-MTDP model
provides a basis for the development of novel team 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 on 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.},
	author = {D. V. Pynadath and Tambe, Milind}
}
