Teleological Inference in Structural Causal Models via Intentional Interventions

Researchers introduce a novel approach using Structural Causal Models to infer the intentions of goal-directed agents. By employing 'intentional interventions' and Structural Final Models, the framework can empirically detect agents and discover their underlying purposes.
Computer Science > Artificial Intelligence
Title:Teleological Inference in Structural Causal Models via Intentional Interventions
View PDF HTML (experimental)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.
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Source: arXiv cs.AI Recent










