Reasoning about Actual Causes in Nondeterministic Domains -- Extended Version

TL;DR

This paper extends formal reasoning about actual causes to nondeterministic domains, enabling agents to better understand causation where they lack control or knowledge of environmental choices.

Contribution

It introduces formal notions of 'Certainly Causes' and 'Possibly Causes' for nondeterministic settings and extends situation calculus regression to reason about these causes.

Findings

Formal definitions of 'Certainly Causes' and 'Possibly Causes' introduced.

Extended regression in situation calculus for nondeterministic causation.

Enhanced reasoning capabilities for agents in uncertain environments.

Abstract

Reasoning about the causes behind observations is crucial to the formalization of rationality. While extensive research has been conducted on root cause analysis, most studies have predominantly focused on deterministic settings. In this paper, we investigate causation in more realistic nondeterministic domains, where the agent does not have any control on and may not know the choices that are made by the environment. We build on recent preliminary work on actual causation in the nondeterministic situation calculus to formalize more sophisticated forms of reasoning about actual causes in such domains. We investigate the notions of ``Certainly Causes'' and ``Possibly Causes'' that enable the representation of actual cause for agent actions in these domains. We then show how regression in the situation calculus can be extended to reason about such notions of actual causes.