Colas, Cédric

Automatic Curriculum Learning For Deep RL: A Short Survey

Portelas, R., Colas, C., Weng, L., Hofmann, K., & Oudeyer, P.-Y. (2020) · Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 127

Language as a Cognitive Tool to Imagine Goals in Curiosity-Driven Exploration

Colas, C., Karch, T., Lair, N., Dussoux, J.-M., Moulin-Frier, C., Dominey, P. F., & Oudeyer, P.-Y. (2020) · arXiv

Reinforcement Learning in RoboticsPsychiatry, Mental Health, Neuroscience

Cited by 64

Teacher algorithms for curriculum learning of Deep RL in continuously parameterized environments

Portelas, R., Colas, C., Hofmann, K., & Oudeyer, P.-Y. (2019) · arXiv

Reinforcement Learning in RoboticsAdvanced Bandit Algorithms Research

Cited by 59

Language and culture internalization for human-like autotelic AI

Colas, C., Karch, T., Moulin-Frier, C., & Oudeyer, P.-Y. (2022) · Nature Machine Intelligence

Psychiatry, Mental Health, NeuroscienceSocial Robot Interaction and HRI

Cited by 34

Self-Improving Language Models for Evolutionary Program Synthesis: A Case Study on ARC-AGI

Pourcel, J., Colas, C., & Oudeyer, P.-Y. (2025) · arXiv

Evolutionary Algorithms and ApplicationsTeaching and Learning Programming

Cited by 0

Code-enabled language models can outperform reasoning models on diverse tasks

Zhang, C. E., Colas, C., Poesia, G., Tenenbaum, J. B., & Andreas, J. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0