neurojs is a JavaScript framework designed to enable deep learning and reinforcement learning directly within web environments. The library provides a full machine learning framework implemented in JavaScript that can run inside browsers or Node.js environments. It focuses particularly on reinforcement learning algorithms, enabling developers to create intelligent agents that learn through interaction with simulated environments. The framework supports neural network architectures and reinforcement learning methods such as deep Q-networks and actor-critic algorithms. Several interactive demonstrations included with the project illustrate how neural networks can be used to train agents in simulated tasks, including a browser-based self-driving car example. These demos allow users to visualize how reinforcement learning agents improve their behavior over time as they receive rewards and update their neural networks.
Features
- JavaScript framework for deep learning and reinforcement learning
- Neural network implementation usable in browser environments
- Support for reinforcement learning algorithms such as deep Q-networks
- Replay buffers and advanced training techniques for RL agents
- Interactive demos including self-driving car simulations
- Export and import of trained neural network models