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，我们探讨了四个基本的挑战，在多智能体系统中建模的信任-共存的智能软件代理系统，旨在解决问题，代表他们的人类用户-利用其他代理提供的建议时。第一个是能够识别和处理代理人之间的串通行为（代理人群体集体旨在提供欺骗性信息），例如电子商务应用程序。第二，为界定咨询代理人的社会网络设定条件，以便与适当数量的同行和更有可能提供有价值信息的同行合作。第三个是将代理信任模型投影到两个非常热门但关键的应用程序中，这些应用程序具有动态变化的挑战：交通（车辆代理共享信息以协助管理城市交通）和医疗保健（利用受信任的对等体的社交网络提供信息以教育用户当前的医疗问题）。最后的项目将更密切地关注特定于上下文的信任建模，这表明多代理系统（利他或恶意代理）的组成和用户的倾向（风险规避或风险寻求）将为其他代理的信任建模设置不同的需求。总之，本研究的目的是使智能代理在多智能体环境中，通过新的技术推理共存的其他代理，以提高决策。通过我们的扩展来解决这些关键场景，将会出现一种具有显著适用性的信任建模方法。此外，将出现对有效划分社交网络的赞赏。