To boost the reliability of reinforcement learning models for complex tasks with variability, MIT researchers have introduced a more efficient algorithm for training them. The findings are ...

By optimizing reinforcement-learning algorithms, DeepMind uncovered new details about how dopamine helps the brain learn. By . Karen Hao archive page; January 15, 2020. Neural Pathways Wikimedia ...

A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...

By contrast, this newly proposed safe reinforcement learning algorithm only assumes access to a sparse indicator for catastrophic failure. And it trains a conservative safety critic that ...

Reinforcement learning is a special branch of AI algorithms that is composed of three key elements: an environment, agents, and rewards. By performing actions, the agent changes its own state and ...

Through reinforcement learning, the algorithm considers positive and negative outcomes from previous charging sessions, such as meeting desired charge levels or exceeding peak thresholds.

The ACM award cites contributions from Barto and Sutton that helped make reinforcement learning practical, including policy-gradient methods, a core way for an algorithm to learn how to behave ...