A Dynamic Semantics for Causal Counterfactuals

Kenneth Lai, James Pustejovsky


Abstract
Under the standard approach to counterfactuals, to determine the meaning of a counterfactual sentence, we consider the “closest” possible world(s) where the antecedent is true, and evaluate the consequent. Building on the standard approach, some researchers have found that the set of worlds to be considered is dependent on context; it evolves with the discourse. Others have focused on how to define the “distance” between possible worlds, using ideas from causal modeling. This paper integrates the two ideas. We present a semantics for counterfactuals that uses a distance measure based on causal laws, that can also change over time. We show how our semantics can be implemented in the Haskell programming language.
Anthology ID:
W19-0601
Volume:
Proceedings of the 13th International Conference on Computational Semantics - Student Papers
Month:
May
Year:
2019
Address:
Gothenburg, Sweden
Venue:
IWCS
SIG:
SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–8
Language:
URL:
https://aclanthology.org/W19-0601
DOI:
10.18653/v1/W19-0601
Bibkey:
Cite (ACL):
Kenneth Lai and James Pustejovsky. 2019. A Dynamic Semantics for Causal Counterfactuals. In Proceedings of the 13th International Conference on Computational Semantics - Student Papers, pages 1–8, Gothenburg, Sweden. Association for Computational Linguistics.
Cite (Informal):
A Dynamic Semantics for Causal Counterfactuals (Lai & Pustejovsky, IWCS 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-0601.pdf