Reinforcement learning is a type of machine learning that assigns positive or negative values to certain outcomes.

As a machine learning researcher, I find it fitting that reinforcement learning pioneers Andrew Barto and Richard Sutton were awarded the 2024 ACM Turing Award. What is reinforcement learning?

Reinforcement learning has also had an unexpected impact on neuroscience. The neurotransmitter dopamine plays a key role in reward-driven behaviors in humans and animals.

Reinforcement learning makes a bold claim: All goals can be achieved by designing a numerical signal, called the reward, and having the agent maximize the total sum of rewards it receives.

Reinforcement learning is a subset of machine learning. It enables an agent to learn through the consequences of actions in a specific environment. It can be used to teach a robot new tricks, for ...

Refinforcment learning from human feedback improves large language models and helps AI chatbots more accessible, but that's the tip of the iceberg.

Summary of Reinforcement Learning: Reinforcement Learning is a powerful approach to machine learning that enables agents to learn optimal behaviors through interaction with their environments.

Reinforcement learning is also being used to improve the reasoning capabilities of chatbots. Reinforcement learning’s origins However, none of these successes could have been foreseen in the 1980s.

Reinforcement learning has also had an unexpected impact on neuroscience. The neurotransmitter dopamine plays a key role in reward-driven behaviors in humans and animals.