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Teleological Inference in Structural Causal Models via Intentional Interventions

arXiv cs.AI / 3/20/2026

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Key Points

  • Introduces intentional interventions and a twin structural final model (SFM) to study teleological questions about the goals of a state-aware, goal-directed agent within causal systems.
  • Defines a time-agnostic operator that creates SFMs, linking observed outcomes to the counterfactual conditions of those interventions (what would have happened had the agent not intervened).
  • Reviews limitations of prior approaches to modeling intentional agents in structural causal models and proposes SFMs as a solution.
  • Demonstrates that SFMs can be used to empirically detect agents and to infer their intentions.

Abstract

Structural causal models (SCMs) were conceived to formulate and answer causal questions. This paper shows that SCMs can also be used to formulate and answer teleological questions, concerning the intentions of a state-aware, goal-directed agent intervening in a causal system. We review limitations of previous approaches to modeling such agents, and then introduce intentional interventions, a new time-agnostic operator that induces a twin SCM we call a structural final model (SFM). SFMs treat observed values as the outcome of intentional interventions and relate them to the counterfactual conditions of those interventions (what would have happened had the agent not intervened). We show how SFMs can be used to empirically detect agents and to discover their intentions.