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 17 - REINFORCE|
In this lesson, we look at the policy gradient approach towards solving immediate RL problems. Specifically, we look at the REINFORCE method proposed by Williams. Reference: Williams, R. J. Simple Statistical Gradient Following Algorithms for Connectionist Reinforcement Learning. 1992.
Go to the Course Home or watch other lectures: