Behaviour Explanation via Causal Analysis of Mental States: A Preliminary Report
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 2 of its 41 references that are in the map. First posted on arXiv 16 May 2022.
Builds on
2 of 41 references.
References · 2
Built on by
Not cited yet.
Similar, not cited
Close in wording, no citation either way
- 2022Causal Robot Communication Inspired by Observational Learning Insights
- 2025Causal Reflection with Language Models
- 2024Explainable agency: human preferences for simple or complex explanations ↗
- 2022Understanding the Unforeseen via the Intentional Stance
- 2025Goals and the Structure of Experience
- 2025Generating Causal Explanations of Vehicular Agent Behavioural Interactions with Learnt Reward Profiles
- 2022Causal Explanations for Sequential Decision Making Under Uncertainty
- 2024The Reasons that Agents Act: Intention and Instrumental Goals