Introduction to TF Agents and Deep Q Learning (Reinforcement learning with TensorFlow Agents)

Wei Wei, a Developer Advocate for TensorFlow, introduces TF Agents and walks through how to use the Deep Q Learning model to solve the cartpole environment. Resources: TensorFlow Agents homepage → Train a Deep Q Network with TF Agents Tutorial → TF-Agent DQN example → Reinforcement Learning Lecture Series 2021 (DeepMind x UCL) → Human Level Control Through Deep Reinforcement Learning (DQN) → DeepMind Reverb: a framework for experience replay → Opening up a physics simulator for robotics → Chapters: 00:00 Introduction 00:23 What is TF Agents 1:38 TF Agents system overview 2:56 Deep Q Network (DQN) 4:10 Environment/Task 5:12 Define Q network 5:40 Define the DQN agent 5:49 Define the collect and eval policies 7:13 Set up the Reverb replay buffer 7:38 Define the replay buffer observer 7:54 Create the driver to collect experience 8:09 Inspe