Behaviour Explanation via Causal Analysis of Mental States: A Preliminary Report

TL;DR

This paper extends a formal causal model to include motivations, enabling causal reasoning about mental states and explaining agent behavior in multiagent communication.

Contribution

It introduces a framework that incorporates motivations into causal analysis of mental states, enhancing explanation capabilities beyond prior models.

Findings

Supports causal reasoning about motivational states.

Allows motivation-altering actions to be causes of effects.

Enables explanation of agent behavior in multiagent contexts.

Abstract

Inspired by a novel action-theoretic formalization of actual cause, Khan and Lesp\'erance (2021) recently proposed a first account of causal knowledge that supports epistemic effects, models causal knowledge dynamics, and allows sensing actions to be causes of observed effects. To date, no other study has looked specifically at these issues. But their formalization is not sufficiently expressive enough to model explanations via causal analysis of mental states as it ignores a crucial aspect of theory of mind, namely motivations. In this paper, we build on their work to support causal reasoning about conative effects. In our framework, one can reason about causes of motivational states, and we allow motivation-altering actions to be causes of observed effects. We illustrate that this formalization along with a model of goal recognition can be utilized to explain agent behaviour in communicative multiagent contexts.