Artificial Intelligence Trust Modeling in Multiagent Systems to Streamline Social Networking

在这项研究中，我们的目标是解决当前热门但关键的问题，即使用计算机导致的信息过载，特别是在社交网络环境中。我们的方法是利用人工智能技术：开发用于信任建模、用户建模和多代理协作的新范式，这将为理论研究提供长期的进步，同时为我们在线存在的管理方面的重大突破奠定基础。一个相伴的目标是拥抱人工智能的当前趋势，以利用应用研究在理论和模型的发展中获得最有价值的新见解。为此，我们将介绍几个关键的应用领域(医疗、教育和交通)，作为激励因素和验证我们方法的试验台领域。 研究的中心将是多智能体系统中信任建模的新方法，包括特定于用户的信任评估(特定于信任者)、受信者产生信任的算法、何时从节点请求信任值的推理(协调等待的值)以及将信任建模投影到代理决策规范中。 总而言之，我们不仅将推进人工智能研究，还将向加拿大提供所有组织和个人使用的关键技术，以实现用户之间更有效的在线沟通和协调。这反过来又将大大节省时间和压力，从而改善我们的整体福祉，改善我们的整体经济。相关的日常背景包括大规模开放的在线课程、电子市场、用于社交的在线环境和基于同伴的网络以实现自助。我们还对增强对在线社交的访问感兴趣

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