LEC 23: Advanced Techniques for Deep Reinforcement Learning: Actor-Critic, TD Lambda
Channel: Abhishek Gupta
Date: 10/04/2020

In the 23rd lecture of ECE 8851: Reinforcement Learning, we explore advanced techniques in deep reinforcement learning. Specifically, we delve into Actor-Critic Architectures for Deep Reinforcement Learning, TD Lambda, Path Consistent Learning (PCL), Unified PCL, and Soft Actor-Critic.

These techniques are powerful tools that can improve the accuracy and efficiency of learning in reinforcement learning. Actor-critic architectures combine the benefits of policy-based and value-based methods, while TD Lambda is a technique used to estimate the value function of an environment. Path Consistent Learning (PCL) and Unified PCL are techniques that use dynamic programming approaches to learn optimal value functions, and Soft Actor-Critic is an algorithm that combines value-based and policy-based methods to learn an optimal policy.

In this lecture, we will discuss each of these techniques in detail, including their strengths and limitations. We will also provide examples to illustrate the application of each technique.