Trends in Deep Reinforcement Learning with Kamyar Azizzadenesheli - #560

This article from Practical AI discusses trends in deep reinforcement learning (RL) with Kamyar Azizzadenesheli, an assistant professor at Purdue University. The conversation covers the current state of RL, including its perceived slowing pace due to the prominence of computer vision (CV) and natural language processing (NLP). The discussion highlights the convergence of RL with robotics and control theory, and explores future trends such as self-supervised learning in RL. The article also touches upon predictions for RL in 2022 and beyond, offering insights into the field's trajectory.

• •The field of deep reinforcement learning is discussed.
• •Convergence of RL with robotics and control theory is a key trend.
• •Self-supervised learning approaches in RL are emerging.