Formal and Cognitive Reasoning, Workshop at KI 2017

Beschreibung

Information for real life AI applications is usually pervaded by uncertainty and subject to change, and thus demands for non-classical reasoning approaches. At the same time, psychological findings indicate that human reasoning cannot be completely described by classical logical systems. Explanations may be incomplete knowledge, incorrect beliefs, or inconsistencies.

Knowledge representation offers a rich palette of methods for uncertain reasoning both to describe human reasoning and to model AI approaches. Its many facets like qualitative vs. quantitative reasoning, defeasible and analogical reasoning, argumentation and negotiation in multi-agent systems, causal reasoning for action and planning, as well as nonmonotonicity and belief revision, among many others, have become very active fields of research. Beyond computational aspects, these methods aim to reflect the rich variety of human reasoning in uncertain and dynamic environments.