Deep Reinforcement Learning (Deep RL) in Pytorch

Laura Graesser (Google Brain) and Keng Wah Loon (Machine Zone) will be visiting us from the Bay Area!

Location: Tech Park at Cal Poly

Deep Reinforcement Learning (Deep RL) is a general framework that can be applied to solve sequential decision-based optimization problems, including various video games. After spending two years building many Deep RL algorithms for teaching and application, the result is SLM Lab - a modular framework for Deep RL in PyTorch.

In this workshop, we will cover the basics of RL and some canonical algorithms, then see them in action by training agents with SLM Lab's implementations to solve some classic and Atari problems. By the end, we will have some practical knowledge to continue exploring Deep RL both in theory and in code.

Pizza provided!!!!!

Python experience: intermediate.
Good to have: basic PyTorch and OpenAI
Installation: go through the Installation and Demo sections in the README of https://github.com/kengz/SLM-Lab and you're all set up.

For context of the pace of this workshop and presentation see these past events:

• https://www.meetup.com/NYC-Data-Wranglers/events/238345289/
• https://insights.untapt.com/openai-lab-for-deep-reinforcement-learning-experimentation-6287867eb611
• https://insights.untapt.com/deep-reinforcement-learning-experiments-run-simultaneously-across-openai-and-unity-environments-62587b89e8ee

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The event will be held at Cal Poly, Tech Park (35.3054128,-120.673986) with ample and free parking!

If you enter Cal Poly from Hwy. 1
You are on Highland Drive
Turn LEFT on Mt. Bishop (Before the train trestle)
Turn LEFT into the Technology Park
Proceed to the lower parking lot

Enter through the double doors on the lower level. The conference room is on the left