The Art of Causal Conjecture
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
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
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
Causality analysis in contract violation
RV'10 Proceedings of the First international conference on Runtime verification
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When dealing with a cause, cases involving some effect due to that cause are precious as such cases contribute to what the cause is. They must be reasoned upon if inference about causes is to take place. It thus seems like a good logic for causes would arise from a semantics based on collections of cases, to be called configurations, that gather instances of a given cause yielding some effect(s). Two crucial features of this analysis of causation are transitivity, which is endorsed here, and the event-based formulation, which is given up here in favor of a fact-based approach. A reason is that the logic proposed is ultimately meant to deal with both deduction (given a cause, what is to hold?) and abduction (given the facts, what could be the cause?) thus paving the way to the inference of explanations. The logic developed is shown to enjoy many desirable traits. These traits form a basic kernel which can be modified but which cannot be extended significantly without losing the adequacy with the nature of causation rules.