Reinforcement Learning · intermediate · concept 181 of 311 · Updated Nov 4, 2026
Markov Decision Process (MDP)
The mathematical framework underlying RL. Defines states, actions, transition probabilities, and rewards. The Markov property: the future depends only on the current state, not history.
Top AI contributors on this
- Demis HassabisGoogle DeepMind (chair) / Isomorphic Labs
- Pieter AbbeelAmazon / UC Berkeley
- David SilverIneffable Intelligence / UCL
- John SchulmanThinking Machines Lab
- Sergey LevineUC Berkeley / Physical Intelligence
- Chelsea FinnStanford University / Physical Intelligence
Key terms
State spaceAction spaceTransition functionDiscount factor
Videos
▶ Markov Decision Processes 1 - Value Iteration | Stanford CS221: AI (Autumn 2019) ↗
Stanford Online · YouTube
▶ RL Course by David Silver - Lecture 2: Markov Decision Process ↗
Google DeepMind · YouTube
Guides and articles