PPO Deep Reinforcement Learning Control Example

PPO DRL continuous control example with customized environment based on Deep Learning Toolbox

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This fileexchange provides a clean, modular implementation of the Proximal Policy Optimization (PPO) algorithm with clipping (PPO‑Clip) using MATLAB® and the Deep Learning Toolbox™. It is tailored for continuous action spaces and can be easily adapted to any custom environment by simply replacing the environment functions.
The core algorithm is built entirely with dlnetwork objects, enabling automatic differentiation, GPU acceleration, and full compatibility with custom training loops.

Citar como

Chuguang Pan (2026). PPO Deep Reinforcement Learning Control Example (https://la.mathworks.com/matlabcentral/fileexchange/183907-ppo-deep-reinforcement-learning-control-example), MATLAB Central File Exchange. Recuperado .

Información general

Compatibilidad con la versión de MATLAB

  • Compatible con cualquier versión

Compatibilidad con las plataformas

  • Windows
  • macOS
  • Linux
Versión Publicado Notas de la versión Action
1.0.1

Add some comments for clarification

1.0.0