# Julia code for the book Reinforcement Learning An Introduction(2nd)

**URL:** <https://discourse.julialang.org/t/julia-code-for-the-book-reinforcement-learning-an-introduction-2nd/19190>\
**Category:** Machine Learning\
**Created:** [January 2, 2019, 11:46am UTC](https://discourse.julialang.org/t/julia-code-for-the-book-reinforcement-learning-an-introduction-2nd/19190 "2019-01-02T11:46:55Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![findmyway](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/findmyway/32/4946_2.png) [@findmyway](https://discourse.julialang.org/u/findmyway)\
**Post date:** [January 2, 2019, 11:46am UTC](https://discourse.julialang.org/t/julia-code-for-the-book-reinforcement-learning-an-introduction-2nd/19190/1 "2019-01-02T11:46:55Z")

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> **[GitHub - JuliaReinforcementLearning/ReinforcementLearningAnIntroduction.jl:...](https://github.com/JuliaReinforcementLearning/ReinforcementLearningAnIntroduction.jl)**
>
> Julia code for the book Reinforcement Learning An Introduction - GitHub - JuliaReinforcementLearning/ReinforcementLearningAnIntroduction.jl: Julia code for the book Reinforcement Learning An Intr...

Recently I reproduced most figures on the book _Reinforcement Learning An Introduction_ in Julia. I hope it is helpful to those who are interested in both Julia and RL.

If you also have a background in Python, I’d suggest you to take a rough view of the Python implementation [here](https://github.com/ShangtongZhang/reinforcement-learning-an-introduction). Then you’ll find that by using multiple dispatch, it is very easy to make abstractions of different levels in Julia.