Action Languages Based Actual Causality in Decision Making Contexts

Camilo Sarmiento (1) , Gauvain Bourgne (1) , Katsumi Inoue (2) , Jean-Gabriel Ganascia (1)

1 ACASA - Agents Cognitifs et Apprentissage Symbolique Automatique
2 NII - National Institute of Informatics

Rationally understanding the evolution of the physical world is inherently linked with the idea of causality. It follows that agents based on automated planning have inevitably to deal with causality, especially when considering imputability. However, the many debates around causation in the last decades have shown how complex this notion is and thus, how difficult it is to integrate it with planning. This paper's contribution is to link up two research topics-automated planning and causality-by proposing an actual causation definition suitable for action languages. This definition is a formalisation of Wright's NESS test of causation.

Mots clés: Causality; Actual Causality; Regularity Theories of Causation; Action Languages

Domaines: Intelligence artificielle [cs.AI]

Camilo Sarmiento, Gauvain Bourgne, Katsumi Inoue, Jean-Gabriel Ganascia. Action Languages Based Actual Causality in Decision Making Contexts. The 24th International Conference on Principles and Practice of Multi-Agent Systems, Nov 2022, Valence, Spain. pp.243-259, ⟨10.1007/978-3-031-21203-1_15⟩. ⟨hal-03790817⟩