The independent choice logic for modelling multiple agents under uncertainty
Artificial Intelligence - Special issue on economic principles of multi-agent systems
Causality: models, reasoning, and inference
Causality: models, reasoning, and inference
The Art of Causal Conjecture
Causes and Explanations: A Structural-Model Approach: Part 1: Causes
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Causality and Counterfactuals in the Situation Calculus
Journal of Logic and Computation
Probabilistic reasoning with answer sets
Theory and Practice of Logic Programming
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Cp-logic: A language of causal probabilistic events and its relation to logic programming
Theory and Practice of Logic Programming
Structure-based causes and explanations in the independent choice logic
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Sequences of mechanisms for causal reasoning in artificial intelligence
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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This paper integrates Pearl's seminal work on probability and causality with that of Shafer. Using the language of CP-logic, it transposes Pearl's analysis of interventions and counterfactuals to the semantic context of Shafer's probability trees. This gives us definitions that work not on the level of random variables, but on the level of Humean events. There are some tangible benefits to our approach: we can elegantly handle counterfactuals in the context of cyclic causal relations, and are able to consider interventions that are both more fine-grained and more elaborate than Pearl's.