ModuRL Guide

This guide is for Rust developers who want to build reinforcement learning programs with ModuRL and Candle. It starts with PPO on CartPole, then explains the library types behind that example, stochastic and deterministic actor-critic algorithms, and the value-based DQN and DDQN paths.

The guide assumes basic Rust and Cargo knowledge. It does not teach reinforcement learning or neural networks from first principles.

ModuRL is early, and API stability is not guaranteed. Start with Getting Started to run and assemble a PPO CartPole program. For off-policy stochastic actor training, read Soft Actor-Critic. For deterministic continuous-control training, read Deterministic Actor-Critic Training before choosing DDPG or TD3. For discrete-action value-based training, read Value-Based Training.

The README provides project status and the shortest repository-based commands. Rustdoc provides the precise contracts for public traits, structs, and builders.