Replaces custom RL implementations for routing and scheduling problems. Built on PyTorch and TorchRL to provide a modular, efficient framework for neural combinatorial optimization.
Tech Stack
PythonAI, ML & Data
Why rl4co?
• Built on TorchRL
• Extensive baseline models
• Highly modular architecture
Limitations
• Requires deep RL knowledge
• PyTorch dependency
• Niche application focus
3/5/2026
Last Update
138
Forks
4
Issues
MIT
License
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