Ceteris paribus logic in counterfactual reasoning

TL;DR

This paper introduces a ceteris paribus logic for counterfactual reasoning that adjusts similarity orders in models to exclude unlikely or impossible events, improving the robustness of counterfactual analysis.

Contribution

It develops a novel formal framework for ceteris paribus reasoning in counterfactuals, with multiple interpretations and applications to avoid skewed similarity orders.

Findings

Framework effectively excludes unlikely events from similarity considerations

Allows counterfactual reasoning unaffected by improbable worlds

Extends formal ceteris paribus reasoning to new domains

Abstract

The semantics for counterfactuals due to David Lewis has been challenged on the basis of unlikely, or impossible, events. Such events may skew a given similarity order in favour of those possible worlds which exhibit them. By updating the relational structure of a model according to a ceteris paribus clause one forces out, in a natural manner, those possible worlds which do not satisfy the requirements of the clause. We develop a ceteris paribus logic for counterfactual reasoning capable of performing such actions, and offer several alternative (relaxed) interpretations of ceteris paribus. We apply this framework in a way which allows us to reason counterfactually without having our similarity order skewed by unlikely events. This continues the investigation of formal ceteris paribus reasoning, which has previously been applied to preferences, logics of game forms, and questions in decision-making, among other areas.