Principles of Knowledge Representation and Reasoning

Knowledge Representation and Reasoning (KR&R) is an exciting and well-established field of research in artificial intelligence, and more broadly in compuer science. In KR&R a fundamental assumption is that an agent's knowledge is explicitly represented in a declarative form, suitable for processing by dedicated reasoning engines. This assumption, that much of what an agent deals with is knowledge-based, is common in many modern intelligent systems. Consequently, KR&R has contributed to the theory and practice of many areas in AI, ranging from automated planning to natural language understanding, as well as to fields beyond AI, including databases, software engineering, the semantic web, computational biology, and the development of software agents. Thee KR conference series is the leading forum for the timely, in-depth presentation of progress in the theory and principles underlying the representation and computational management of knowledge. It is intended to foster communication and a crossfertilization of ideas within the area, as well as collaboration across research boundaries. As a consequence, the topics addressed at KR 2016, in common with previous KR conferences, are diverse and cover a broad range of research areas. For KR 2016 the most popular topics included argumentation, description logics, belief change and nonmonotonicity, epistemic reasoning, spatial and temporal reasoning, and, in a significant increase from previous years, KR and data management.