rl and rsrl
These are competitors—both are general-purpose reinforcement learning frameworks in Rust that serve the same use case, with rsrl being more mature and widely adopted (4x the stars, 3x the downloads).
About rl
benbaarber/rl
A rust reinforcement learning library
This library helps machine learning engineers and researchers quickly develop and test reinforcement learning agents. It takes in various environment definitions and produces trained agents capable of making decisions, along with tools for logging and visualizing training progress. The primary users are those building and experimenting with AI agents for tasks like game playing or robotic control.
About rsrl
tspooner/rsrl
A fast, safe and easy to use reinforcement learning framework in Rust.
This project helps Rust developers quickly build and experiment with reinforcement learning systems. You provide details about your problem's environment and desired agent behavior, and it outputs an agent capable of learning optimal actions through interaction. It's ideal for software engineers, machine learning engineers, or researchers working with Rust.
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