Belief change in rational agents

理性主体的信念改变

• 批准号: 884-2007
• 负责人: Delgrande, James
• 金额: $ 2.4万
• 依托单位: Simon Fraser University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2007
• 资助国家: 加拿大
• 起止时间: 2007-01-01 至 2008-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=362491
• 关键词: Belief; change; rational; agents

In Knowledge Representation (KR) in Artificial Intelligence, an agent deals with a problem domain which could be a specific problem area (such as diagnosis), a physical domain (such as encountered by a robot) or a "virtual" domain (such as provided by the web). In all such cases, the agent's knowledge will generally be incomplete, inaccurate to some extent, and constantly changing. An important problem in KR is to manage this change of information, whether the agent has been told a new fact, or has carried out some actions, or has been given a set of observations from different sources.The main focus of this research is on belief change, which deals with how an agent should modify its beliefs on the basis of new information. While much work has been carried out, there are crucial issues that have yet to be fully addressed. For example, it is not clear that the formal models that we have fully characterize all aspects of belief change; as well, there is no agreement as to how an agent should incorporate a sequence of observations about a fixed environment. This research will address the problem of belief change, and the wider problem of reasoning in a dynamic world of agents that can carry out actions. First, mathemetical models characterizing aspects of belief change will be developed, and second, complementary to this, computational models will be developed and studied in the context of their applicability in different areas.A secondary, but strongly related, topic of research concerns reasoning with preferences. Typically an agent will have not just (strict) goals to attain, but also things that are desirable, but not necessary, to establish. The use of preferences in planning, as well as the role of preferences in belief change, will also be addressed.

在人工智能的知识表示（KR）中，智能体处理的问题域可以是特定的问题区域（如诊断），物理域（如机器人遇到的）或“虚拟”域（如由Web提供的）。在所有这些情况下，代理人的知识通常是不完整的，在某种程度上是不准确的，并且不断变化。在KR中的一个重要问题是管理这种信息的变化，无论是代理人已经被告知一个新的事实，或已执行一些行动，或已被给予一组观察从不同的sources.The主要焦点研究的信念变化，它涉及代理人应该如何修改其信念的基础上的新信息。虽然已经开展了许多工作，但仍有一些关键问题尚未得到充分解决。例如，我们所拥有的正式模型是否能充分表征信念变化的所有方面，这一点并不清楚;同样，对于一个主体应该如何整合一系列关于固定环境的观察结果，也没有达成一致。这项研究将解决信念变化的问题，以及在一个动态的世界中，可以执行行动的代理推理的更广泛的问题。首先，将开发表征信念变化方面的理论模型，其次，作为补充，将开发计算模型，并在不同领域的适用性方面进行研究。第二，但密切相关的研究主题涉及偏好推理。通常，一个智能体不仅要达到（严格的）目标，而且还要建立一些可取但不必要的东西。在规划中使用的偏好，以及在信念变化的偏好的作用，也将得到解决。