Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent ought to take ...

Deep · Temporal difference learning · Q-learning · Markov decision process

Q-learning is a model-free reinforcement learning algorithm to learn the value of an action in a particular state. It does not require a model of the ...

In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent to human preferences.

Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning.

It is an area of machine learning inspired by behaviorist psychology. Reinforcement learning is different from supervised learning because the correct inputs ...

In behavioral psychology, reinforcement refers to consequences that increase the likelihood of an organism's future behavior, typically in the presence of a ...

Multi-agent reinforcement learning (MARL) is a sub-field of reinforcement learning. It focuses on studying the behavior of multiple learning agents that ...