摘要翻译：
动态多Agent环境中的Agent必须监视其对等体以执行单个和组计划。一个关键的开放问题是需要对其他代理的状态进行多大程度的监控才能有效：监控选择性问题。我们在协作Agent团队中的失败检测的背景下研究这个问题，通过社会关注监控，关注Agent之间社会关系中的失败监控。我们在两个动态的、复杂的、多Agent领域中，在不同的任务分配和不确定性条件下，实证和分析地探索了一族社会关注的团队协作监控算法。我们表明，使用复杂算法的集中式方案以正确性换取完整性，并要求监视所有队友。相比之下，一个简单的分布式团队监控算法可以正确和完整地检测团队失败，尽管依赖于有限的、不确定的知识，并且只监控团队中的关键代理。此外，我们还报告了一个社会关注监控系统的设计，并展示了它在监控几种协调关系、诊断检测到的故障以及在线和离线应用中的通用性。
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英文标题：
《Robust Agent Teams via Socially-Attentive Monitoring》
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作者：
G. A. Kaminka, M. Tambe
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最新提交年份：
2011
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Multiagent Systems        多智能体系统
分类描述：Covers multiagent systems, distributed artificial intelligence, intelligent agents, coordinated interactions. and practical applications. Roughly covers ACM Subject Class I.2.11.
涵盖多Agent系统、分布式人工智能、智能Agent、协调交互。和实际应用。大致涵盖ACM科目I.2.11类。
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一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  Agents in dynamic multi-agent environments must monitor their peers to execute individual and group plans. A key open question is how much monitoring of other agents' states is required to be effective: The Monitoring Selectivity Problem. We investigate this question in the context of detecting failures in teams of cooperating agents, via Socially-Attentive Monitoring, which focuses on monitoring for failures in the social relationships between the agents. We empirically and analytically explore a family of socially-attentive teamwork monitoring algorithms in two dynamic, complex, multi-agent domains, under varying conditions of task distribution and uncertainty. We show that a centralized scheme using a complex algorithm trades correctness for completeness and requires monitoring all teammates. In contrast, a simple distributed teamwork monitoring algorithm results in correct and complete detection of teamwork failures, despite relying on limited, uncertain knowledge, and monitoring only key agents in a team. In addition, we report on the design of a socially-attentive monitoring system and demonstrate its generality in monitoring several coordination relationships, diagnosing detected failures, and both on-line and off-line applications.
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PDF链接：
https://arxiv.org/pdf/1106.0235