Linked from

The 21 pages that link to Reinforcement learning, each with the reason it gives.

• RoboticsRelated: Some robots learn control policies through repeated interaction with environments.

• Basal gangliaRelated: Dopamine signals help basal ganglia circuits update action choices from outcomes.

• LearningRelated: It formalizes reward-guided learning in artificial agents.

• Social learningRelated: Social cues can supply information about rewards even before direct experience.

• Artificial general intelligenceRelated: It offers methods for learning behavior through interaction and feedback.

• Computational neuroscienceRelated: It provides mathematical tools for modeling reward-guided learning in brains.

• Artificial intelligence in video gamesRelated: It can train agents through repeated gameplay rather than hand-authored rules.

• Richard BellmanRelated: Its value functions and learning algorithms draw directly on Bellman’s equations.

• Computer GoRelated: Self-play lets Go programs learn strategies from the consequences of their moves.

• Demis HassabisRelated: It underlies many DeepMind systems developed during Hassabis’s leadership.

• NeuroeconomicsRelated: Its prediction errors link reward experience to changes in later choices.