Reinforcement learning is a subfield of machine learning concerned with how an intelligent agent can learn through trial and error to make optimal decisions in its ...

Reinforcement learning is one of the exciting branches of artificial intelligence. It plays an important role in game-playing AI systems, modern robots, chip-design systems, and other applications.

Positive reinforcement involves adding something good after a behavior to make it happen more often. Reinforcement works best when given right after the behavior happens to keep the right connections.

Using a bunch of carrots to train a pony and rider. (Photo by: Education Images/Universal Images Group via Getty Images) Andrew Barto and Richard Sutton are the recipients of the Turing Award for ...

Reinforcement learning algorithms help AI reach goals by rewarding desirable actions. Real-world applications, like healthcare, can benefit from reinforcement learning's adaptability. Initial setup ...

Some of the most common tools parents and teachers use for managing children’s behaviors are rewards and punishments. While these methods tend to lose effectiveness as a child ages, there are times ...

Operant conditioning, sometimes called instrumental conditioning or Skinnerian conditioning, is a method of learning that uses rewards and punishment to modify behavior. Through operant conditioning, ...

Operant conditioning is a theory that explains how behaviors are influenced by their consequences or results. It’s often used today to help people adopt new behaviors or change old habits. If you’ve ...