Real time Reinforcement learning examples

Over the last 4 months, I’ve completed several different projects using Reinforcement learning on a dynamixel servo providing real time continuous sensorimotor data to the learning algorithms. In particular, I’ve experimented with creating, running, and measuring thousands of GVF demons making predictions in parallel, policy gradient actor critic methods, and pavlovian control.

I’ve attempted to document what I learned as best as I could. All code and experimental writeups can be found on my github page at:

www.github.com/dquail/RobotPerception

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s