Implementing an Intelligent - Autonomous Car Driving Agent using Deep Actor-Critic Algorithm

In Chapter 6, Implementing an Intelligent Agent for Optimal Control using Deep Q-Learning, we implemented agents using deep Q-learning to solve discrete control tasks that involve discrete actions or decisions to be made. We saw how they can be trained to play video games such as Atari, just like we do: by looking at the game screen and pressing the buttons on the game pad/joystick. We can use such agents to pick the best choice given a finite set of choices, make decisions, or perform actions where the number of possible decisions or actions is finite and typically small. There are numerous real-world problems that can be solved with an agent that can learn to take optimal through to discrete actions. We saw some examples in Chapter 6, Implementing an Intelligent Agent for Optimal Discrete...