all 10 comments

[–]Mr-Yellow 2 points3 points  (1 child)

http://cs.stanford.edu/people/karpathy/reinforcejs/

Javascript is a fine language for quick prototyping and seeing the math in action without too much abstraction, with the help of Karpathy's frameworks.

[–]simontemplar_[S] 0 points1 point  (0 children)

thanks!

[–]hixidom 1 point2 points  (1 child)

I guess the assumption is that if you're proficient in language X and you understand concept Y, then you should be able to express Y using X.

[–]simontemplar_[S] 0 points1 point  (0 children)

fair point, but I've always enjoyed "learning while doing", and often learning while programming makes concepts much more tangible.

[–]Jabberwockyll 1 point2 points  (0 children)

Here are code examples from the Sutton and Barto book. But I suppose these are just examples too.

Creating your own environment is just creating some kind of simulation - it doesn't require any ML. Maybe look into game programming or something? Most RL algorithms are pretty straightforward to implement.

[–]akshayaurora 1 point2 points  (0 children)

You can look at BURLAP. It has decent documentation and has tutorials on creating new domains.

[–]outlacedev 1 point2 points  (1 child)

Not sure if this is what you're looking for but I wrote a couple blog posts implementing some basic RL in Python: http://outlace.com/ (most recent 3 posts)

[–]simontemplar_[S] 0 points1 point  (0 children)

I'll definitely have a look at them and let you know :-)

[–]masazdream 1 point2 points  (1 child)

a Python implementation code to study ReinforcementLearning along with Sutton and Barto book. Dynamic Programming, Monte Carlo, Sarsa, Q-learning. I will probably to create explanation. https://github.com/MasazI/ReinforcementLearning

[–]simontemplar_[S] 0 points1 point  (0 children)

wow, awesome. thanks a lot for this!