OpenAI Gym: Toolkit for developing, comparing reinforcement learning algorithms

PLE as well! https://github.com/ntasfi/PyGame-Learning-Environment

(disclaimer I'm the author)

Unfortunately RL Glue is not nearly as good as it looks or sounds. I was thinking about using it to solve some problems I have (for example, I was interested in modeling embryo selection for complex traits as a POMPD to see what the optimal approaches might be rather than settling for a simple calculation as I did in http://www.gwern.net/Embryo%20selection ), but the project is abandoned, and while it implements an interface/IPC glue, there are few implementations of any interesting environments or useful agents, so you would wind up writing everything yourself anyway. Once I got the simple tabular agent example working, I went looking at the more complex ones and was quite disappointed.

From the description in OP, it already far exceeds RL Glue's usefulness.

And then hook up cryptocurrency payments so the AI can pay for upgrades.

It looks like this system allows easy comparison of reinforcement learning techniques [those techniques can be implemented using any major ML framework].

So it isn't a competitor to Tensorflow, it sort of allows you to measure techniques built using Tensorflow [or Theano etc]. And the metrics are "how general is this technique?" "how effective is this technique?"

Essentially, lots of research says "this technique is effective at this problem," but there is often no way to compare it to other leading techniques in the field. This playground sort of puts everyone on the same playing field.

[and since it's open, it seems you can add your own environments. Like if you want to build a Chess AI using reinforcement learning, you can add a chess environment to this playground]

Gym's potential is to be a starting point for a community around OpenAI. There are far more smart people in the world eager to demonstrate their ability, than there are experts directly employed in AI today.

Over 5000 teams around the world submitted solutions to the Netflix prize[1]. OpenAI is a far more important project. They should be able to drive even greater enthusiasm and participation.

[1] http://www.netflixprize.com/leaderboard

Agree! Down the road, Kaggle will be the Kaggle for RL algorithms ;) This provides a really cool open source environment to build on

>> Evaluations: We've made it easy to upload results to OpenAI Gym. However, we've opted not to create traditional leaderboards. What matters for research isn't your score (it's possible to overfit or hand-craft solutions to particular tasks), but instead the generality of your technique.

https://openai.com/blog/openai-gym-beta/

From the link:

> we've opted not to create traditional leaderboards. What matters for research isn't your score (it's possible to overfit or hand-craft solutions to particular tasks), but instead the generality of your technique.

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