沟通型多智能体团队决策问题：团队工作理论与模型分析
The Communicative Multiagent Team Decision Problem: Analyzing Teamwork Theories and Models
摘要：
尽管多智能体团队合作取得了重大进展，现有的研究并没有解决其处方的最优性，也没有团队合作问题的复杂性。如果没有最优性-复杂性权衡的表征，就不可能确定特定理论所做的假设和近似是否获得了足够的效率来证明整体性能的损失。为了提供一个工具，用于多智能体研究人员在评估这种权衡，我们提出了一个统一的框架，通信多智能体团队决策问题（COM-MTDP）。COM-MTDP模型结合并扩展了现有的多智能体理论，如分散的部分可观察马尔可夫决策过程和经济团队理论。COM-MTDP除了具有一般性的表示外，还支持团队绩效最优性和Agent决策问题的计算复杂性分析。在分析复杂性，我们提出了一个细分的计算复杂性的问题域的各种类别下，沿尺寸的可观察性和通信成本构建最佳团队。在分析最优性，我们利用COM-MTDP的能力，现有的团队合作的理论和模型编码两个实例的联合意图理论从文献中。此外，COM-MTDP模型提供了一个新的团队协调算法的发展基础。我们推导出一个独立于域的最佳通信标准，并提供了一个比较分析的两个联合意图的实例就这个最佳的政策。我们已经实现了一个可重用的，独立于域的软件包COM-MTDP的基础上分析团队合作的协调策略，我们证明了它的使用编码和评估的两个联合意图的策略在一个例子域。
英文摘要：
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.
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