Skip to main content

Python Research Toolkit - Reinforcement Learning

Project description

My code related to learning and using RL outside of a specific project

The documentation website is at https://reinforcement-learning.readthedocs.io/

Installation

Installing prt-rl from pypi as:

pip install prt-rl

Getting Started

Related Libraries

Reference RL Repositories

Contributing

Contributions are welcome, but please submit an issue prior to submitting a PR so the feature or bug can be discussed. This repository follows semantic versioning with the format major.minor.patch. The patch version bumping is automatically handled by the action workflow, and major/minor bumps can be performed by adding #major or #minor to the commit message. The tag must be in the commit short message for the action to correctly pick it up.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

prt_rl-0.3.0.tar.gz (13.8 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

prt_rl-0.3.0-py3-none-any.whl (47.9 kB view details)

Uploaded Python 3

File details

Details for the file prt_rl-0.3.0.tar.gz.

File metadata

  • Download URL: prt_rl-0.3.0.tar.gz
  • Upload date:
  • Size: 13.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.7.2

File hashes

Hashes for prt_rl-0.3.0.tar.gz
Algorithm Hash digest
SHA256 5623e3398331c8775305796fe3a29518f5152e76b14f60e581fddf7a9b297a0f
MD5 ad5f38252cb8b5b6a4d5518afd29c10a
BLAKE2b-256 f62e7efdd09ead8e6ffe82ff049d27bc6d3dc5f3f1472a86c40f5547533b8510

See more details on using hashes here.

File details

Details for the file prt_rl-0.3.0-py3-none-any.whl.

File metadata

  • Download URL: prt_rl-0.3.0-py3-none-any.whl
  • Upload date:
  • Size: 47.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.7.2

File hashes

Hashes for prt_rl-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 22a16b5ab6befe7db5dce841e30f5f34b2a34fcdd531eb268a9db1b99ffe7b88
MD5 095a8b4eededb54c7191ce67bbd5f9ad
BLAKE2b-256 db35d3d94a6b5fa6d62dd84196f5808f24bcbb8ac0e339b4081950c177f60b33

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page