Skip to main content

A simple RL library.

Project description

# A simple agent trained to play LunarLander using Policy Gradients

This project is still a work in progress. More algorithms and detailed documentation coming soon :)

To run the code- ` python3 main.py `

Requirements- ` gym==0.10.5 matplotlib==2.2.3 tensorflow==1.6.0 `

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

RLkit-0.1.tar.gz (4.3 kB view details)

Uploaded Source

File details

Details for the file RLkit-0.1.tar.gz.

File metadata

  • Download URL: RLkit-0.1.tar.gz
  • Upload date:
  • Size: 4.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.20.0 setuptools/40.5.0 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/2.7.12

File hashes

Hashes for RLkit-0.1.tar.gz
Algorithm Hash digest
SHA256 f7f9a21de64c46cf97e1635fb33efe8f69c6dba029ebc47c61319b0663337f00
MD5 8a4e8629dedab99982dd60afd4148b7f
BLAKE2b-256 667062b6cf04c17c64e28c923ff216cdb658df60b85bab5d5e812b8c5561307b

See more details on using hashes here.

Supported by

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