在坚持不懈的团队中实现灵活的团队合作

Milind Tambe, Weixiong Zhang
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引用次数: 100

摘要

团队协作是多智能体环境中的一项关键能力。许多这样的环境要求代理和代理团队必须是持久的,即在很长一段时间内存在。这种持久团队中的代理人被他们长期的共同利益和目标联系在一起。本文关注的是这种持久团队中的灵活团队合作。不幸的是,虽然以前的工作已经研究了灵活的团队合作,但持久的团队仍未被探索。对于灵活的团队合作,一种有前景的方法是基于模型的,即为代理提供团队合作的一般模型,明确指定他们在团队合作中的承诺。这些模型使代理能够自主地对协调进行推理。不幸的是,对于坚持不懈的团队来说,这样的模型可能会导致协调和沟通行为,尽管这些行为在局部是最优的,但对于团队的长期目标来说却是非常有问题的。我们提出了一种决策理论技术,使持久团队能够克服基于模型方法的这种限制。特别地,智能体会对团队合作模型所推荐的行动以及这些行动的低成本(或高成本)变化所预测的未来团队状态的预期团队效用进行推理。为了适应实时约束,这种推理可以随时进行。给出了一个分析搜索树和一些实际领域的实现实例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards flexible teamwork in persistent teams
Teamwork is a critical capability in multi-agent environments. Many such environments mandate that the agents and agent-teams mast be persistent i.e., exist over long periods of time. Agents in such persistent teams are bound together by their long-term common interests and goals. This paper focuses on flexible teamwork in such persistent teams. Unfortunately, while previous work has investigated flexible teamwork, persistent teams remain unexplored. For flexible teamwork, one promising approach that has emerged is model-based, i.e., providing agents with general models of teamwork that explicitly specify their commitments in teamwork. Such models enable agents to autonomously reason about coordination. Unfortunately, for persistent teams, such models may lead to coordination and communication actions that while locally optimal, are highly problematic for the team's long-term goals. We present a decision-theoretic technique to enable persistent teams to overcome such limitations of the model-based approach. In particular, agents reason about expected team utilities of future team states that are projected to result from actions recommended by the teamwork model, as well as lower-cost (or higher-cost) variations on these actions. To accommodate real-time constraints, this reasoning is done in an any-time fashion. Implemented examples from an analytic search tree and some real-world domains are presented.
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