Modeling cognitive processes within a creative problem-solving task: from symbolic to neuro-symbolic approaches in computational learning sciences
C Mercier - 2024 - theses.hal.science
Integrating transversal skills such as creativity, problem solving and computational thinking,
into the primary and secondary curricula is a key challenge in today's educational field. We …
into the primary and secondary curricula is a key challenge in today's educational field. We …
[PDF][PDF] Algorithmic ersatz for VSA: Macroscopic simulation of Vector Symbolic Architecture
C Mercier, T Viéville - neurosymbolic-ai-journal.com
Spiking neuronal networks are biologically plausible implementations of brain circuit
computations, meaning that they can provide a way to manipulate symbols embedded as …
computations, meaning that they can provide a way to manipulate symbols embedded as …
Analyse de la motivation intrinsèque au cours d'une activité de résolution de problèmes.
L Denet - 2021 - inria.hal.science
On cherche ici à aider des chercheuses et chercheurs en sciences du numérique
(informatique et mathématiques appliquées), des neurosciences cognitives et des sciences …
(informatique et mathématiques appliquées), des neurosciences cognitives et des sciences …
Early Empirical Results on Reinforcement Symbolic Learning
Reinforcement learning is a subfield of machine learning that is concerned with how agents
learn to make decisions in an environment in order to maximize some notion of reward. It …
learn to make decisions in an environment in order to maximize some notion of reward. It …