HCC: Collaborative Research: Information Exchange and Social Factors in Human-Computer-Teamwork Decision Making

这个项目解决了决策战略设计的核心问题，使计算机代理能够有效地与不同群体中的人合作，这些群体在开展复杂活动时相互作用。这些人和系统的混合网络出现在各种各样的真实世界应用中，以及用于培训的虚拟现实和模拟系统中。它们发生在计算机系统支持共同工作的人的环境中，发生在计算机系统充当个人代理的环境中，发生在代理组自主(但与人一起)执行他们负责的组成任务的环境中。尽管混合网络被广泛使用，但与仅由计算机代理组成的多代理系统的代理设计相比，能够在这种环境下运行的代理的设计受到的关注较少。混合网络中的人的加入为自治代理决策机制的设计提出了新的问题。这项建议侧重于以下三个挑战，这些挑战在以前的工作中没有得到充分的研究，代理设计者必须解决这些挑战，以构建能够在混合网络中与人类合作伙伴良好工作的系统：(1)针对代理能力和过去行为的信息交换策略；(2)协作交互的中断管理机制的设计；以及(3)学习社会因素和组织结构的模型并将其纳入决策机制。

This project addresses problems central to the design of decision-making strategies that enable computer agents to work effectively with people in heterogeneous groups that interact in carrying out complex activities. These mixed networks of people and systems arise in a wide variety of real-world applications as well as in virtual reality and simulation systems used for training. They occur in settings in which computer systems support people who are working together, those in which they act as proxies for individual people, and those in which groups of agents act autonomously (but alongside people) to carry out constituent tasks for which they are responsible. Despite mixed networks being wide spread, the design of agents that can operate in such settings has received less attention than the design of agents for multi-agent systems comprising only computer agents.The inclusion of people in mixed networks presents novel problems for the design of autonomous agent decision-making mechanisms. This proposal focuses on the following three of these challenges, which have not been investigated sufficiently in prior work and which agent designers must address to construct systems able to work well with their human partners in mixed networks: (1) information exchange policies for agent competence and past behavior; (2) design of interruption management mechanisms for collaborative interactions; and, (3) learning and incorporation of models of social factors and organizational structures into decision-making mechanisms.