MIT 6.S094: Deep Reinforcement Learning for Motion Planning

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Apr 28, 2025

This is lecture 2 of course 6.S094: Deep Learning for Self-Driving Cars taught in Winter 2017. This lecture introduces types of machine learning, the neuron as a computational building block for neural nets, q-learning, deep reinforcement learning, and the DeepTraffic simulation that utilizes deep reinforcement learning for the motion planning task. INFO: Slides: http://bit.ly/2H8Fs7g Website: https://deeplearning.mit.edu GitHub: https://github.com/lexfridman/mit-dee... Playlist: https://goo.gl/SLCb1y Links to individual lecture videos for the course: Lecture 1: Introduction to Deep Learning and Self-Driving Cars • MIT 6.S094: Introduction to Deep Lear... Lecture 2: Deep Reinforcement Learning for Motion Planning • MIT 6.S094: Deep Reinforcement Learni... Lecture 3: Convolutional Neural Networks for End-to-End Learning of the Driving Task • MIT 6.S094: Convolutional Neural Netw... Lecture 4: Recurrent Neural Networks for Steering through Time • MIT 6.S094: Recurrent Neural Networks... Lecture 5: Deep Learning for Human-Centered Semi-Autonomous Vehicles • MIT 6.S094: Deep Learning for Human-C... CONNECT: If you enjoyed this video, please subscribe to this channel. AI Podcast: https://lexfridman.com/ai/ LinkedIn: / lexfridman Twitter: / lexfridman Facebook: / lexfridman Instagram: / lexfridman Slack: https://deep-mit-slack.herokuapp.com