Skip to main content

Quint is a minimal path finding library useful for discrete state scenarios

Project description

No hassle Q-learning library

Quint is a minimal path finding library useful for discrete state scenarios

Usage

  • Install : pip install quint

  • Import : from quint import quint

  • Instantiate : model = quint(reward_matrix, gamma) (refer quint docstring for matrix structure)

  • Override quint.act() to your own action function

  • Learn : model.learn(final_state, iterations)

  • Trace : model.find_optimum_path(from_state)

MIT License

Copyright (C) 2014 Abhinav Tushar

Project details


Release history Release notifications | RSS feed

This version

0.1

Download files

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

Source Distribution

quint-0.1.zip (4.8 kB view details)

Uploaded Source

File details

Details for the file quint-0.1.zip.

File metadata

  • Download URL: quint-0.1.zip
  • Upload date:
  • Size: 4.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for quint-0.1.zip
Algorithm Hash digest
SHA256 c26af20099fdc94ee4ea60e1a105a09389cade9d6a3fe4303518006484b9bd7c
MD5 4739846d410f69fd879de849f77486e1
BLAKE2b-256 ae3c2ccbacc763c1fc4e1628f061e23f95ae83f1a39ec4856164e24fa399b3a6

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