AI029
Reinforcement Learning: An Introduction
Finite Markov Decision Processes
Learning Objectives
- Define the agent-environment interface and the interaction loop.
- Formally define Finite Markov Decision Processes (MDPs).
- Understand the role of goals, rewards, and returns in task formulation.
- Identify the significance of the Markov property in state representation.