Interventions in possibilistic logic

Publication Type:
Conference Proceeding
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009, 5785 LNAI pp. 40 - 54
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An intervention is a tool that enables us to distinguish between causality and simple correlation. The use of interventions has been only implemented in Bayesian net structures (or in their possibilistic counterpart) until now. The paper proposes an approach to the representation and the handling of intervention-like pieces of knowledge, in the setting of possibilistic logic. It is compatible with a modeling of the way agents perceive causal relations in reported sequences of events, on the basis of their own beliefs about how the world normally evolves. These beliefs can also be represented in a possibilistic logic framework. © 2009 Springer Berlin Heidelberg.
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