Explore the strengths and limitations of symbolic and connectionist AI as well as the challenges AI faces in replicating human experience and reasoning.

This article explores two major approaches to artificial intelligence: symbolic AI, based on logical rules, and connectionist AI, inspired by neural networks. Beyond the technical aspects, the aim is to question concepts such as perception and cognition and to reflect on the challenges that AI must take up to better manage contradictions and aim to imitate human thought.

Preamble

French researcher Sébastien Konieczny was recently named EuAI Fellow 2024 for his groundbreaking work on belief fusion and inconsistency management in artificial intelligence. His research, focused on reasoning modeling and knowledge revision, opens up new perspectives to enable AI systems to tend to reason even more reliably in the face of contradictory information, and thus better manage the complexity of the real world.

Konieczny's work is part of a wider context of reflection and fundamental questioning about the very nature of artificial intelligence. These questions are at the root of ...