The Communicative Multiagent Team Decision Problem: Analyzing Teamwork Theories and Models

Abstract

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. 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.

Coordinating Teams in Uncertain Environments: A Hybrid BDI-POMDP Approach

“…In order to do quantitative analysis of key coordination decisions in multiagent teams, we extend Multiagent Team Decision Problem (MTDP) [30] for the analysis of the coordination actions of interest. For example, the COM-MTDP [30] is an extension of MTDP for the analysis of communication.…”

“…For example, the COM-MTDP [30] is an extension of MTDP for the analysis of communication. In this paper, we illustrate a general methodology for analysis of other aspects of coordination and present the RMTDP model for quantitative analysis of role allocation and reallocation as a concrete example.…”

“…Given a team of n agents, an MTDP [30] is defined as a tuple: S, A, P, Ω, O, R . It consists of a finite set of states S = Ξ 1 × · · · × Ξ m where each Ξ j , 1 ≤ j ≤ m, is a feature of the world state.…”

“…Fortunately, the emergence of distributed Partially Observable Markov Decision Problems (POMDPs) provides models [3,4,30,43] that are well-suited for quantitative analysis of agent teams in uncertain domains. These models are powerful enough to express the uncertainty in these dynamic domains and in principle, can be used to generate and evaluate complete policies for the multiagent team.…”

“…In general, each agent's policy in a distributed POMDP is indexed by its observation history [3,30]. However, in a BDI system, each agent performs its action selection based on its set of privately held beliefs which is obtained from the agent's observations after applying a belief revision function.…”