Reinforcement Learning. Instructor: Prof. Balaraman Ravindran, Department of Computer Science and Engineering, IIT Madras. Reinforcement learning is a paradigm that aims to model the trial-and-error learning process that is needed in many problem situations where explicit instructive signals are not available. It has roots in operations research, behavioral psychology and AI. The goal of the course is to introduce the basic mathematical foundations of reinforcement learning, as well as highlight some of the recent directions of research. (from nptel.ac.in)
|Lecture 19 - Full RL Introduction|
Having looked at the immediate RL problem, we now start our discussion on the full RL problem. In this lesson, we will cover the components of a full RL system. We will look at states and actions, the agent-environment interface, rewards, and policies.
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