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MIT 6.S094: Deep Reinforcement Learning
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This is lecture 3 of course 6.S094: Deep Learning for Self-Driving Cars (2018 version). This class is free and open to everyone. It is an introduction to the practice of deep learning through the applied theme of building a self-driving car.
OUTLINE:
0:00 - AI Pipeline from Sensors to Action
8:25 - Reinforcement Learning
23:50 - Deep Reinforcement Learning
36:00 - AlphaGo
41:50 - DeepTraffic
54:35 - Conclusion
INFO:
CONNECT:
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LINKS:
2017:
OUTLINE:
0:00 - AI Pipeline from Sensors to Action
8:25 - Reinforcement Learning
23:50 - Deep Reinforcement Learning
36:00 - AlphaGo
41:50 - DeepTraffic
54:35 - Conclusion
INFO:
CONNECT:
- If you enjoyed this video, please subscribe to this channel.
LINKS:
2017:
MIT 6.S094: Deep Reinforcement Learning for Motion Planning
MIT 6.S094: Deep Reinforcement Learning
MIT 6.S094: Introduction to Deep Learning and Self-Driving Cars
MIT 6.S094: Deep Learning
MIT 6.S091: Introduction to Deep Reinforcement Learning (Deep RL)
MIT 6.S094: Recurrent Neural Networks for Steering Through Time
MIT 6.S094: Deep Learning for Human-Centered Semi-Autonomous Vehicles
MIT 6.S094: Convolutional Neural Networks for End-to-End Learning of the Driving Task
MIT 6.S094: Deep Learning for Human Sensing
MIT 6.S094: Computer Vision
MIT 6.S191 (2023): Reinforcement Learning
Deep Learning Basics: Introduction and Overview
DeepTraffic Game (6.S094: Deep Learning for Self-Driving Cars)
DeepTraffic Solution | MIT: Deep Learning for Self-Driving Cars
MIT 6.S191 (2020): Reinforcement Learning
Lex Fridman: Is Reinforcement Learning a Good Candidate for AGI?
Deep Reinforcement Learning Nanodegree Program
MIT 6.S191 (2019): Deep Reinforcement Learning
Overview of Deep Reinforcement Learning Methods
MIT 6.S191 (2022): Reinforcement Learning
16. Reinforcement Learning, Part 1
MIT DeepTraffic 2.0 competition solution
Learning to perch a UAV on the ground using deep reinforcement learning
CS 285: Lecture 1, Part 1
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