Knowledge Representation, Reasoning, and Declarative Problem Solving
Knowledge Representation, Reasoning, and Declarative Problem Solving
Causes and Explanations: A Structural-Model Approach: Part 1: Causes
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Artificial Intelligence - Special issue on logical formalizations and commonsense reasoning
The DLV system for knowledge representation and reasoning
ACM Transactions on Computational Logic (TOCL)
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Causes and explanations: a structural-model approach-part II: explanations
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Ontology-based inference for causal explanation
Integrated Computer-Aided Engineering
Cost-sensitive Iterative Abductive Reasoning with abstractions
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
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We define an inference system to capture explanations based on causal statements, using an ontology in the form of an IS-A hierarchy. We first introduce a simple logical language which makes it possible to express that a fact causes another fact and that a fact explains another fact. We present a set of formal inference patterns from causal statements to explanation statements. These patterns exhibit ontological premises that are argued to be essential in deducing explanation statements. We provide an inference system that captures the patterns discussed.