What does Reinforcement Learning mean? Definition | AI Understanding

Definition

Training by reward signals where an agent learns actions that maximize long-term return.

Related terms

Reinforcement Learning from Human Feedback (RLHF)

A training method that uses human preference signals to shape model behavior.

A model that scores outputs based on preference signals, often used in RLHF pipelines.

A software system that can observe, reason, and take actions to achieve a goal, often using tools and memory.

Constitutional AI

A training and behavior-shaping approach where model outputs are guided by a fixed set of written principles.

An iterative cycle where an AI agent observes, plans, acts, and reflects until it completes a goal or hits a stop condition.

DPO (Direct Preference Optimization)

A training method that fine-tunes models directly on preference pairs without needing a separate reward model.

Learn more in our free guides

Deep Learning Reinforcement Learning Machine Learning Basics Supervised Learning

See also

Red Teaming Recommendation System Retrieval Recall RAG (Retrieval-Augmented Generation)Robustness Quantization Safety Filter

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