gold
A reinforcement learning library for Go providing agents, composable tooling, and visualization for solving environment challenges.
What is gold?
Gold is a reinforcement learning library for Go that provides a collection of agents and tools for solving challenges in various environments. It implements algorithms like Q Learning, Deep Q Learning, and Proximal Policy Optimization, along with composable tooling for building custom agents and visualizing their performance. The library is designed to be simple to hack on and integrates with other Go-based ML projects.
Go developers and researchers interested in implementing and experimenting with reinforcement learning algorithms, particularly those who prefer working in Go's ecosystem.
Gold offers a straightforward, modular approach to reinforcement learning in Go, with multiple pre-built agents and visualization tools. Its composable design and integration with libraries like Sphere and Goro make it practical for both learning and prototyping RL solutions.
Overview
Reinforcement Learning in Go
Use Cases
Best For
- Implementing Q Learning or Deep Q Learning agents in Go
Related Projects
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