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#selfdriving, #carla, #qlearning, #pytorch In this lecture we enter the realm of autonomous driving by making use of the Carla simulator and implementing deep q-learning networks in pytorch. The task is to control the steering of a self driving agent. This lecture is only an introduction to doing self driving in this manner (for end to end autonomous systems), and as we learn more reinforcement learning & deep learning algorithms, we'll improve our agent's performance. Stay tuned. You can find the code referenced in this lecture in the following repository: https://github.com/JabrahTutorials/Re... The agent was trained for about 7-8 hours, just to show its capability to learn in this environment. Reference: This paper inspired the approach taken https://link.springer.com/article/10.... 0:00 Intro 1:50 Problem Setup 6:20 Reward Function Design 16:45 Image Processing 20:45 Architecture 29:40 Challenges in RL Design 34:20 Programming Solution