معرفی
Jean-Louis Dessalles is a Lecturer at Télécom Paris within the Information Processing and Communication Laboratory (LTCI) and Data, Intelligence and Graphs (DIG) research team. His work bridges Artificial Intelligence, Cognitive Science, and Evolutionary Biology, focusing on modeling human communication through his Simplicité Theory (Simplicity Theory). This framework explains narrative interest and argumentative relevance via complexity drops, serving as a foundation for understanding language evolution as a social signaling game.
- Education: École Polytechnique (1976), Télécom Paris diploma (1981), Doctorate (1993), and Habilitation (2008) from Université Paris-Sorbonne.
His research spans causal learning in cyber-physical systems, argumentation modeling through conflict-abduction-negation (CAN) procedures, and evolutionary origins of language. Recent work includes decentralized XAI architectures for smart homes and non-Euclidean analogy frameworks. He has authored seminal books like Why We Talk (Oxford, 2007) and Des intelligences TRÈS artificielles (Odile Jacob, 2019).
Scientific Contributions:
- Causal Modeling: Developed scalable Bayesian network learning via interventions in smart home systems.
- Simplicity Theory: Demonstrated how unexpectedness drives narrative interest and communication relevance.
- Human-AI Interaction: Proposed decentralized architectures for explainable AI in multi-agent environments.
