Reinforcement learning

How it is used

Shortened to RL. Its key words are agent, environment, action, reward and policy. It is used in game-playing systems, robotics and recommendations, and in the RLHF stage that makes LLMs more helpful.

Example sentences

1. The warehouse robots were first trained with reinforcement learning in a simulator.

2. Designing the reward is the hardest part of any reinforcement learning project.

Common collocations

• reinforcement learning agent
• deep reinforcement learning
• reward function
• RL environment

Related terms

• RLHFShort for reinforcement learning from human feedback: a training stage in which people rank model answers, a reward model learns their preferences, and the LLM is then tuned to score higher.
• supervised learningA type of machine learning in which the model learns from examples that come with correct answers (labels), so that it can predict the answer for new examples.
• unsupervised learningA type of machine learning that finds structure in data without correct answers (labels), for example grouping similar customers or spotting unusual events.
• AI agentA system built around an LLM that can plan steps and use tools, such as search, code or company software, to complete a task with little human help.

This word in other fields

The same English word can have a different meaning in another field:

• reinforcement learning · Software Engineering

More terms: Machine Learning Basics

• artificial intelligence
• machine learning
• model
• classification
• regression
• clustering
• state-of-the-art