Artificial Intelligence Trust Modeling in Multiagent Systems to Streamline Social Networking

多代理系统中的人工智能信任建模可简化社交网络

• 批准号: RGPIN-2016-03615
• 负责人: Cohen, Robin
• 金额: $ 2.77万
• 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: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=687064
• 关键词: Artificial; Intelligence; Trust; Modeling; Multiagent

In this research, we aim to address the current topical but critical problem of information overload arising from the use of computers, especially in social networking environments. Our approach is to leverage artificial intelligence techniques: to develop novel paradigms for trust modeling, user modeling and multiagent cooperative coordination which will provide longstanding advances to theoretical research while at the same time forming the basis for significant breakthroughs in the management of our online existence. A companion aim is to embrace the current trend in artificial intelligence to leverage applied research towards the most valuable new insights in the development of theories and models. Towards this end, we will introduce several key application areas (healthcare, education and transportation) as motivators and as testbed areas for validation of our approach.**Central to the research will be novel methods for trust modeling in multiagent systems, including user-specific trust evaluation (specific to the trustor), algorithms for trustees to engender trust, reasoning about when to solicit trust values from peers (the value of coordinated waiting), and projecting trust modeling into a specification of agent decision making.**In all, we will not only advance artificial intelligence research but will also offer to Canada techniques of critical use to all organizations and individuals to enable more effective online communication and coordination between users. This in turn will translate into significant savings in time and in stress, towards an improvement of our overall state of wellbeing, to improve our overall economy. Relevant everyday contexts include massively open online courses, electronic marketplaces, online environments for social communication and peer-based networking to enable self-help. We are also interested in enabling enhanced access to online social

在这项研究中，我们旨在解决使用计算机，尤其是在社交网络环境中引起的当前信息超负荷的主题问题。我们的方法是利用人工智能技术：为信任建模，用户建模和多种合作协调开发新颖的范式，这将为理论研究提供长期的进步，同时为在我们在线存在的管理中的重大突破构成基础。伴侣的目的是拥抱人工智能的当前趋势，以利用应用研究来实现理论和模型发展中最有价值的新见解。为此，我们将介绍几个关键的应用领域（医疗保健，教育和运输）作为验证我们方法的动力和测试领域。代理决策的规范。反过来，这将转化为及时和压力的大量节省，以改善我们整体福祉状况，以改善我们的整体经济。相关的日常环境包括大规模开放的在线课程，电子市场，在线环境的社交沟通和基于同伴的网络以实现自助。我们也有兴趣增强在线社交的访问