FOR 1513: Hybrid Reasoning for Intelligent Systems (HYBRIS)

知识表示和推理（KR&R），特别是对行为、行为的影响和行为发生的环境的推理，是智能行为的基础，从一开始就一直是人工智能的核心问题。到目前为止，大多数KR&R方法都集中在定性表示上，这与许多应用领域的要求形成鲜明对比，这些应用领域也需要处理定量信息。这种定量方面的例子是时间、概率不确定性、多标准优化或质量等资源。这个研究单位的目的是整合定性和定量形式的推理，导致混合推理形式主义。这项工作将建立在以前DFG资助的项目集群“基于逻辑的知识表示”的结果之上，其中一些最成功的定性KR&R形式主义与对行动推理的关注相结合。为了增加拟议研究的实际影响和相关性，来自两个精心挑选的应用领域，机器人技术和生物信息学的专家是该联盟的一部分，将开展基础和应用驱动的项目。从长远来看，研究部门将朝着扩大KR&R技术作为大型复杂智能系统的一部分的使用迈出一大步。

Knowledge Representation and Reasoning (KR&R) and, in particular, reasoning about actions, their effects and the environment in which actions take place, are fundamental for intelligent behaviour and have been a central concern in artificial intelligence from the beginning. To date, most KR&R approaches have focussed on qualitative representations, which contrasts with requirements from many application domains where quantitative information needs to be processed as well. Examples of such quantitative aspects are time, probabilistic uncertainty, multi-criteria optimisation or resources like mass. The aim of this Research Unit is to integrate both qualitative and quantitative forms of reasoning, resulting in hybrid reasoning formalisms. The work will build on the results from the previous DFG-funded project cluster "Logic-Based Knowledge Representation", where some of the most successful qualitative KR&R formalisms were combined with a focus on reasoning about actions. To increase the practical impact and relevance of the proposed research, experts from two carefully selected application areas, robotics and bioinformatics, are part of the consortium, and both foundational and application-driven projects will be carried out. In the long run, the Research Unit will take a big step towards widening the use of KR&R technology as part of large, complex intelligent systems.