With the development of several new directions of AI, including explainable AI, ethical AI and knowledge-based AI, the corresponding directions of logical research are gaining momentum: causal reasoning, reasoning with norms and values, and knowledge graph reasoning. In an open and dynamic environment, the main challenges for modeling such kinds of reasoning are to deal with information that is typically incomplete, uncertain, dynamic and conflicting, and to effectively explain the results and procedures of reasoning to ...
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With the development of several new directions of AI, including explainable AI, ethical AI and knowledge-based AI, the corresponding directions of logical research are gaining momentum: causal reasoning, reasoning with norms and values, and knowledge graph reasoning. In an open and dynamic environment, the main challenges for modeling such kinds of reasoning are to deal with information that is typically incomplete, uncertain, dynamic and conflicting, and to effectively explain the results and procedures of reasoning to ordinary human beings. Nonmonotonic logics and formal argumentation can be used as fundamental theories to cope with these challenges. The papers in this volume report some recent advantages of the research on related topics.
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