Abstract
Causality and belief changes play an important role in many applications. Recently, Pearl [6] has proposed approaches based on probability theory using causal graphs to give formal semantics to the notion of interventions. From representational point of view, interventions are distinguished from observations using the concept of the ”do” operator [4]. From reasoning point of view, handling interventions consists in ”ignoring” the effects of all direct (and undirected) causes related to the variable of interest.
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References
Benferhat, S., Smaoui, S.: Possibilistic causal networks for handling interventions: A new propagation algorithm. In: Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence (AAAI 2007), Vancouver, British Columbia, pp. 373–378 (2007)
Dubois, D., Prade, H.: Possibility theory: An approach to computerized, Processing of uncertainty. Plenium Press, New York (1988)
Gärdenfors, P.: Knowledge in Flux: Modeling the Dynamics of Epistemic States. Bradford Books. MIT Press, Cambridge (1988)
Goldszmidt, M., Pearl, J.: Rank-based systems: A simple approach to belief revision, belief update, and reasoning about evidence and actions. In: Proceeding of the Third International Conference (KR 1992), pp. 661–672. Kaufmann, San Francisco (1992)
Katsuno, H., Mendelzon, A.: Propositional Knowledge Base Revision and Minimal Change. Artificial Intelligence 52, 263–294 (1991)
Pearl, J.: Causality: models, reasoning, and inference. Cambridge University Press, New York (2000)
Spohn, W.: Ordinal conditional functions: a dynamic theory of epistemic states causation in decision. In: Harper, W., Skyrms, B. (eds.) Belief Changes and Statistics, pp. 105–134 (1988)
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Benferhat, S. (2007). Causality and Dynamics of Beliefs in Qualitative Uncertainty Frameworks. In: Mellouli, K. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2007. Lecture Notes in Computer Science(), vol 4724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75256-1_2
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