Shypd.aiThe largest open index of AI toolsneural-combinatorial-rl-pytorch is an Open Source & Models tool that provides a PyTorch implementation for neural combinatorial optimization with reinforcement learning. It includes a basic RL pretraining model and supports tasks like sorting and the Traveling Salesperson Problem.
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neural-combinatorial-rl-pytorch offers a PyTorch implementation of Neural Combinatorial Optimization with Reinforcement Learning, based on the research paper. This open-source tool provides a basic RL pretraining model that utilizes greedy decoding. A notable feature is its use of an exponential moving average critic instead of a traditional critic network, which has been shown to significantly improve results, particularly for the Traveling Salesperson Problem (TSP). The implementation supports a stochastic decoding policy during training and beam search for testing. It currently includes support for a sorting task and the planar symmetric Euclidean TSP, with clear guidelines for extending it to other combinatorial optimization problems by providing a dataset class and a reward function. The repository also details dependencies and provides performance results for both TSP and sorting tasks, demonstrating its generalization capabilities.
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