IJCAI 2023poster3 citations
A Rule-Based Modal View of Causal Reasoning
Abstract
We present a novel rule-based semantics for causal reasoning as well as a number of modal languages interpreted over it. They enable us to represent some fundamental concepts in the theory of causality including causal necessity and possibility, interventionist conditionals and Lewisian conditionals. We provide complexity results for the satisfiability checking and model checking problem for these modal languages. Moreover, we study the relationship between our rule-based semantics and the structural equation modeling (SEM) approach to causal reasoning, as well as between our rule-based semantics for causal conditionals and the standard semantics for belief base change.
Knowledge Representation and Reasoning: KRR: Knowledge representation languagesKnowledge Representation and Reasoning: KRR: CausalityKnowledge Representation and Reasoning: KRR: Reasoning about knowledge and belief
BibTeX
@inproceedings{ijcai2023p366,
title = {A Rule-Based Modal View of Causal Reasoning},
author = {Lorini, Emiliano},
booktitle = {Proceedings of the Thirty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-23}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Edith Elkind},
pages = {3286--3295},
year = {2023},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2023/366},
url = {https://doi.org/10.24963/ijcai.2023/366},
}