KR 2022

Knowledge Representation and Reasoning (KR) is a well-established and lively field of research. In KR 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 has contributed to the theory and practice of various areas in AI, including automated planning and natural language understanding, and to fields beyond AI, including databases, verification, software engineering, and robotics. In recent years, KR has contributed also to new and emerging fields, including the semantic web, computational biology, cyber security, and the development of software agents.

The KR conference series is the leading forum for timely in-depth presentation of progress in the theory and principles underlying the representation and computational management of knowledge. 

Topics of interest include, but are not limited to:

• Applications of KR
• Argumentation
• Belief revision and update, belief merging
• Commonsense reasoning
• Computational aspects of knowledge representation
• Concept formation, similarity-based reasoning
• Contextual reasoning
• Decision making
• Description logics
• Explanation finding, diagnosis, causal reasoning, abduction
• Geometric, spatial, and temporal reasoning
• Inconsistency- and exception-tolerant reasoning
• KR and autonomous agents and multi-agent systems
• KR and cognitive modelling
• KR and cognitive reasoning
• KR and cognitive robotics
• KR and cognitive systems
• KR and cyber security
• KR and education
• KR and game theory
• KR and machine learning, inductive logic programming, knowledge acquisition
• KR and natural language processing and understanding
• KR and the Web, Semantic Web
• Knowledge graphs and open linked data
• Knowledge representation languages
• Logic programming, answer set programming
• Modeling and reasoning about preferences
• Multi- and order-sorted representations and reasoning
• Nonmonotonic logics, default logics, conditional logics
• Ontology formalisms and models
• Ontology-based data access, integration, and exchange
• Philosophical foundations of KR
• Qualitative reasoning, reasoning about physical systems
• Reasoning about actions and change, action languages
• Reasoning about constraints, constraint programming
• Reasoning about knowledge, beliefs, and other mental attitudes
• Uncertainty, vagueness, many-valued and fuzzy logics