Articles in category “Reinforcement Learning”
Markov Decision Processes - The Framework For Decision-Making Under Uncertainty
Markov Decision Processes are the essential process which we use in dynamic programming and thus reinforcement learning problems. It is an extension of Markov chains and provides the theoretical backbone for training an AI agent under iterative environments and rewards based off of decisions.
K-Armed Bandits: The Canonical RL Problem
The main toy problem behind reinforcement learning
What is Reinforcement Learning?
Key RL concepts and history
Reinforcement Learning Notes
Some Reinforcement Learning Notes Based off of the book by Sutton.
