Informati on for real life AI applications is usually pervad ed by uncertainty and subject to change, and thus demands for non-classical reasoning approaches. At the same time, psychological findings indicate th at human reasoning cannot be completely described by classical logical systems. Sources of explanati ons are incomplete knowledge, incorrect beliefs, o r inconsistencies. A wide range of reasoning mecha nism has to be considered, such as analogical or d efeasible reasoning. The field of knowledge repres entation and reasoning offers a rich palette of me thods for uncertain reasoning both to describe hum an reasoning and to model AI approaches.
\n\nThe aim of this series of workshops is to addre ss recent challenges and to present novel approach es to uncertain reasoning and belief change in the ir broad senses, and in particular provide a forum for research work linking different paradigms of reasoning.
\nWe welcome origi nal papers on any of the workshop topics or relate d topics. We put a special focus on papers from bo th fields that provide a base for connecting forma l-logical models of knowledge representation and c ognitive models of reasoning and learning, address ing formal as well as experimental or heuristic is sues.
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