lsunsi/markovjs

Reinforcement Learning in JavaScript

42
/ 100
Emerging

This tool helps you experiment with basic reinforcement learning models directly in JavaScript. You can define a 'game' with states, actions, and rewards, and then train an agent to learn the best actions over time. It takes your game rules and desired learning parameters as input, and outputs an agent that can make decisions within your simulated environment. This is for developers, researchers, or students interested in building and understanding reinforcement learning agents.

No commits in the last 6 months. Available on npm.

Use this if you want a clear, minimal JavaScript implementation to understand or prototype simple reinforcement learning problems, without deep mathematical complexity.

Not ideal if you need a high-performance, production-ready, or mathematically advanced reinforcement learning framework, as it's designed more as a foundational playground.

reinforcement-learning algorithm-development simulation agent-modeling machine-learning-prototyping
Stale 6m
Maintenance 0 / 25
Adoption 9 / 25
Maturity 25 / 25
Community 8 / 25

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Stars

76

Forks

4

Language

JavaScript

License

MIT

Last pushed

Dec 03, 2016

Commits (30d)

0

Dependencies

1

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