Trust and social networking of multiagent peers

多智能体对等体的信任和社交网络

• 批准号: 880-2011
• 负责人: Cohen, Robin
• 金额: $ 1.46万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=543913
• 关键词: Trust; social; networking; multiagent; peers

In this research, we explore four fundamental challenges to modeling trust in multiagent systems -- systems of co-existing intelligent software agents that are designed to problem solve on behalf of their human users -- when making use of advice provided by other agents. The first is to be able to identify and address collusive behaviour among agents (where groups of agents collectively aim to provide deceptive information) for example for e-commerce applications. The second is to set the conditions for delimiting the social network of advising agents, in order to operate with an appropriate number of peers and with peers that have a greater likelihood of being able to provide information of value. The third is to project models of agent trust into two very topical but critical applications with challenges of dynamic change: that of transportation (vehicular agents sharing information to assist in the management of urban traffic) and healthcare (leveraging a social network of trusted peers to provide information to educate a user about a current medical problem). The final project will look more closely at context-specific trust modeling, suggesting that the makeup of the multiagent system (altruistic or malicious agents) and the proclivity of the user (risk averse or risk seeking) will set differing demands for the trust modeling of other agents. In all, this research aims to enable improved decision making by intelligent agents in multiagent environments through novel techniques for reasoning about the other agents that co-exist. With our extensions to address these critical scenarios what will emerge is a methodology for trust modeling that has a significant reach of applicability. In addition, an appreciation for effective delimiting of social networks will emerge.

在这项研究中，我们探讨了对多种系统的信任建模的四个基本挑战，即在使用其他代理商提供的建议时，旨在代表其人类用户解决问题的智能软件代理系统。首先是能够识别和解决代理商之间的犯罪行为（代理人集体旨在提供欺骗性信息），例如用于电子商务应用程序。第二个是设定界定咨询代理商的社交网络的条件，以便与适当数量的同龄人一起操作，并且具有更大有可能提供价值信息的同行。第三个是将代理信托的模型投影到两个非常局部但至关重要的应用程序中，具有动态变化的挑战：运输的挑战（车辆代理共享信息以帮助管理城市交通的管理）和医疗保健（利用受信任的同伴的社交网络来提供信息，以教育用户有关当前医疗问题的信息）。最终项目将更加仔细研究特定于上下文的信任建模，这表明多种系统的构成（无私或恶意代理），用户的倾向（避开风险或风险寻求风险）将设定对其他代理商信任建模的不同需求。总的来说，这项研究旨在通过新颖的技术来推理共存的其他代理，从而使智能代理在多种环境中改善决策。通过我们的扩展解决这些关键方案，将出现的一种信任建模的方法，具有很大的适用性。此外，将出现对有效划定社交网络的欣赏。