MIT 6.S094: Deep Reinforcement Learning for Motion Planning
发布时间 2017-01-22 16:34:30 来源
摘要
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-deep-learning
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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