Deep learning, reinforcement learning, and world models

Deep learning (DL) and reinforcement learning (RL) methods seem to be a part of indispensable factors to achieve human-level or super-human AI systems. On the other hand, both DL and RL have strong connections with our brain functions and with neuroscientific findings. In this review, we summarize talks and discussions in the "Deep Learning and Reinforcement Learning" session of the symposium, International Symposium on Artificial Intelligence and Brain Science. In this session, we discussed whether we can achieve comprehensive understanding of human intelligence based on the recent advances of deep learning and reinforcement learning algorithms. Speakers contributed to provide talks about their recent studies that can be key technologies to achieve human-level intelligence.

# Reinforcement Learning in Robotics # Computer Science # Psychiatry, Mental Health, Neuroscience # Domain Adaptation and Few-Shot Learning

Yutaka Matsuo, Yann LeCun, Maneesh Sahani, et al. (2022). "Deep learning, reinforcement learning, and world models". Neural Networks. https://doi.org/10.1016/j.neunet.2022.03.037