Abstract
The objective of this paper is to study causal inference as an issue of common sense reasoning. It is well known that causal inference cannot be represented by classical implication which has a number of properties not correct for causal implication, such as monotonicity, contraposition or transitivity. In several fields of artificial intelligence, causality has been represented in different ways, by conditional-type operators [5],[9],[10], by modal operators [2],[14],[6], by meta-rules [13],[3] and by means of non-logical predicates [7].
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Schwind, C. (1999). A Theory for Causal Reasoning. In: Burgard, W., Cremers, A.B., Cristaller, T. (eds) KI-99: Advances in Artificial Intelligence. KI 1999. Lecture Notes in Computer Science(), vol 1701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48238-5_24
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DOI: https://doi.org/10.1007/3-540-48238-5_24
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