RL Framework

This page covers the core RL framework you need for the preliminary assessment: the four main components, the Markov property, exploration vs exploitation, and the discount factor. Back to Preliminary. Why this matters for RL Every RL problem is defined by who acts (agent), what they interact with (environment), what they observe (state), what they can do (actions), and what feedback they get (reward). The Markov property and the discount factor shape how we define value functions and algorithms. Exploration vs exploitation is the central tension in learning from experience. ...