"Belief change in rational agents (with application to action formalisms, ontologies, and inferentially weak systems)"

在人工智能中的知识表示（KR）中，智能体的知识通常是不完整的，可能是不准确的，并且是不断发展的。无论代理是物理领域中的机器人，还是网络上的软件代理，还是处理医疗信息语料库的推理代理，都将是这种情况。KR中的一个关键问题是管理这些变化的信息，无论这些变化是来自于被告知的新事实，还是某些执行行动的结果，还是来自于对环境的感知。拟议研究的重点将是管理信念的变化。虽然在行为推理和信念修正方面已经开展了大量工作，但仍有一些关键问题尚未得到充分解决或尚未完全理解。例如，我们所拥有的信念修正模型是否完全描述了信念改变的所有方面，这一点尚不清楚；此外，研究直到最近才涉及到特殊用途的KR语言的变化，例如涉及Horn理论或本体论的语言。在之前的资助期间，工作重点是信念变化的基础，重点是迭代变化算子和推理弱系统中的变化，以及在偏好和非单调推理的相关领域的工作。在即将到来的拨款期内，我将继续研究信念改变的基础，但也将处理三个具体的相互关联的项目，这些项目与信念改变在现实环境中的应用有关。第一个项目（与来自SFU、希腊和澳大利亚的同事）将研究描述逻辑中的信念变化，特别是用于表示医学本体的逻辑，以及所谓的语义网。第二个项目（与来自多伦多的同事合作）将提供一个完整的高级代理规范，该代理能够合并有关已知动作效果的信息、被告知的信息和传感器信息，其目标是能够修改其知识，无论不正确的知识是来自不正确的信息、不可靠的传感器还是失败的操作。第三个项目（与SFU的一位同事合作）将解决大规模（海上）和当地（家庭辅助生活）环境中的态势感知问题。

In Knowledge Representation (KR) in Artificial Intelligence, an agent's knowledge will generally be incomplete, possibly inaccurate, and evolving. This will be the case whether the agent is a robot in a physical domain, or a software agent on the web, or a reasoning agent dealing with a corpus of medical information. A crucial problem in KR is to manage such changing information, whether change comes from being told a new fact, or as a result of some executed action, or from sensing the environment. The focus of the proposed research will be on managing belief change. While much work has been carried out in the areas of reasoning about action and belief revision, there are crucial issues that have not been fully addressed or that are not fully understood. For example, it is not clear that the models that we have for belief revision fully characterize all aspects of belief change; as well, research has only recently addressed change in special-purpose KR languages, such as those involving Horn theories or ontologies. Work in the previous grant period focused on the foundations of belief change, with emphasis on iterated change operators and change in inferentially weak systems, along with work in the related areas of preferences and nonmonotonic reasoning. For the coming grant period I will continue working on the foundations of belief change, but also will address three specific interrelated projects concerned with the application of belief change in realistic settings. The first project (with colleagues from SFU, Greece, and Australia) will examine belief change in description logics, specifically with logics used for representing medical ontologies on the one hand, and the so-called semantic web of the other. The second project (with a colleague from Toronto) will be to provide a full high-level specification of an agent able to incorporate information about known action effects, being informed of something, and sensor information, with the goal of being able to revise its knowledge, whether the incorrect knowledge came from incorrect information, fallible sensors, or failed actions. The third project (with a colleague from SFU) will address situational awareness in large-scale (maritime) and local (household assisted living) settings.