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MIT 6.S094: Deep Reinforcement Learning for Motion Planning

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Published on Jan 22, 2017

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.

Course website: http://cars.mit.edu
Lecture 2 slides: https://goo.gl/r2LYv0
Contact: deepcars@mit.edu

Playlist: https://goo.gl/SLCb1y

Links to individual lecture videos for the course:

Lecture 1: Introduction to Deep Learning and Self-Driving Cars
https://youtu.be/1L0TKZQcUtA

Lecture 2: Deep Reinforcement Learning for Motion Planning
https://youtu.be/QDzM8r3WgBw

Lecture 3: Convolutional Neural Networks for End-to-End Learning of the Driving Task
https://youtu.be/U1toUkZw6VI

Lecture 4: Recurrent Neural Networks for Steering through Time
https://youtu.be/nFTQ7kHQWtc

Lecture 5: Deep Learning for Human-Centered Semi-Autonomous Vehicles
https://youtu.be/ByZF8_-OJNI

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