Showing 4 open source projects for "q-learning"

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    The HaskellR project

    The HaskellR project

    The full power of R in Haskell

    The HaskellR project provides an environment for efficiently processing data using Haskell or R code, interchangeably. HaskellR allows Haskell functions to seamlessly call R functions and vice versa. It provides the Haskell programmer with the full breadth of existing R libraries and extensions for numerical computation, statistical analysis and machine learning. Optionally, pass in the --nix flag to all commands if you have the Nix package manager installed. Nix can populate a local build...
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    purescript

    purescript

    A strongly-typed language that compiles to JavaScript

    Compile to readable JavaScript and reuse existing JavaScript code easily. An extensive collection of libraries for development of web applications, web servers, apps and more. Excellent tooling and editor support with instant rebuilds. An active community with many learning resources. Build real-world applications using functional techniques and expressive types, such as: Algebraic data types and pattern matching. Row polymorphism and extensible records. Higher kinded types and type classes...
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  • 3
    IHaskell

    IHaskell

    A Haskell kernel for the Jupyter project

    IHaskell is a kernel for the Jupyter project, which allows you to use Haskell inside Jupyter frontends (including the console and notebook). It currently supports GHC 8.0 through 9.0. For GHC 7.10 support please use the GHC7 tag. For a tour of some IHaskell features, check out the demo Notebook. More example notebooks are available on the wiki. The wiki also has more extensive documentation of IHaskell features. IHaskell is based upon the IPython architecture and frontend, so learning about...
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  • 4
    Procreator is a framework for genetic programming written in Haskell. Procreator generates fully typed programs. This will allow for more effective crossover and for better compilation of the generated programs.
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