Abstract
AbstractIn knowledge representation and reasoning, a key area in artificial intelligence research, non-classical logics play a prominent double role: firstly, non-classical logic languages allow for a precise and transparent encoding of domain specific knowledge. Secondly, as the logical languages are equipped with custom-tailored rules of logical inference, they make available a principled approach to derive new knowledge from previous information. In practice, the first aspect addresses data storage and retrieval, the second aspect the utilization of available information. This article briefly surveys contemporary challenges of NCL research in AI.
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