No
Yes
View More
View Less
Working...
Close
OK
Cancel
Confirm
System Message
Delete
Schedule
An unknown error has occurred and your request could not be completed. Please contact support.
Scheduled
Wait Listed
Personal Calendar
Speaking
Conference Event
Meeting
Interest
Schedule TBD
Conflict Found
This session is already scheduled at another time. Would you like to...
Loading...
Please enter a maximum of {0} characters.
Please enter a maximum of {0} words.
must be 50 characters or less.
must be 40 characters or less.
Session Summary
We were unable to load the map image.
This has not yet been assigned to a map.
Search Catalog
Reply
Replies ()
Search
New Post
Microblog
Microblog Thread
Post Reply
Post
Your session timed out.
This web page is not optimized for viewing on a mobile device. Visit this site in a desktop browser to access the full set of features.
2017 GTC San Jose

S7381 - DeepTraffic: Driving Fast through Dense Traffic with Deep Reinforcement Learning

Session Speakers
Session Description

This talk will introduce DeepTraffic, a deep reinforcement learning competition at MIT that has received over 10,000 submissions and is preparing for its second iteration. It's accessible to both beginners and experts. Whether with Javascript or TensorFlow, the task is to drive faster than anyone else in the world. We will introduce deep reinforcement learning through the case study of motion planning in dense micro-traffic simulation, and describe the emergent behavior achieved through crowdsourced hyper-parameter tuning of policy networks. Go deep, go fast at http://selfdrivingcars.mit.edu.


Additional Session Information
All
Talk
Deep Learning and AI Self-Driving Cars
Automotive
50 minutes
Session Schedule