#function #approximation #linear #ai #rl

lfa

Native rust implementations of linear function approximators

30 releases (15 breaking)

0.15.0 Jun 7, 2020
0.14.0 Mar 17, 2020
0.13.0 Aug 31, 2019
0.12.1 May 4, 2019
0.2.1 Feb 21, 2018

#1443 in Rust patterns

Download history 40/week @ 2023-10-23 78/week @ 2023-10-30 31/week @ 2023-11-06 52/week @ 2023-11-13 59/week @ 2023-11-20 114/week @ 2023-11-27 29/week @ 2023-12-04 32/week @ 2023-12-11 63/week @ 2023-12-18 118/week @ 2023-12-25 20/week @ 2024-01-01 27/week @ 2024-01-08 23/week @ 2024-01-15 50/week @ 2024-01-22 75/week @ 2024-01-29 20/week @ 2024-02-05

172 downloads per month
Used in rsrl

MIT license

120KB
3K SLoC

LFA (api)

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Overview

lfa provides a set of implementations for common linear function approximation techniques used in reinforcement learning.

Installation

[dependencies]
lfa = "0.15"

Note that rsrl enables the blas feature of its ndarray dependency, so if you're building a binary, you additionally need to specify a BLAS backend compatible with ndarray. For example, you can add these dependencies:

blas-src = { version = "0.2.0", default-features = false, features = ["openblas"] }
openblas-src = { version = "0.6.0", default-features = false, features = ["cblas", "system"] }

See ndarray's README for more information.

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate and adhere to the angularjs commit message conventions (see here).

License

MIT

Dependencies

~2.5MB
~39K SLoC