Reinforcement learning · MLD-0211
Contextual bandit
A decision problem selecting actions from observed context and receiving feedback without full long-horizon state dynamics.
Original reference page · detailed expansion pending. Original definitions, examples, notes and citations are preserved below. New examples are illustrative, not benchmark results.
Original example
Choose a recommendation and observe a click.
Original caveat
Delayed or state-changing effects can violate the bandit simplification.
Context and aliases
Level: Intermediate. Stages: Theory · Training · Evaluation.
Tags: RL · DL · SLM · LLM.
Aliases: None recorded.
Related concepts
Concepts linking here
Original references
- OpenAI Spinning Up: reinforcement learning ↗ · Consulted
- TRL documentation ↗ · Consulted
- Original reference URL ↗