Ant Colony Sampling with GFlowNets for Combinatorial Optimization

• URL: http://arxiv.org/abs/2403.07041v3
• Date: Fri, 11 Oct 2024 11:36:39 GMT
• Title: Ant Colony Sampling with GFlowNets for Combinatorial Optimization
• Authors: Minsu Kim, Sanghyeok Choi, Hyeonah Kim, Jiwoo Son, Jinkyoo Park, Yoshua Bengio,
• Abstract summary: Generative Flow Ant Colony Sampler (GFACS) is a novel meta-heuristic method that hierarchically combines amortized inference and parallel search. Our method first leverages Generative Flow Networks (GFlowNets) to amortize a multi-modal prior distribution over a solution space.
• Score: 68.84985459701007
• License:
• Abstract: We present the Generative Flow Ant Colony Sampler (GFACS), a novel meta-heuristic method that hierarchically combines amortized inference and parallel stochastic search. Our method first leverages Generative Flow Networks (GFlowNets) to amortize a multi-modal prior distribution over combinatorial solution space that encompasses both high-reward and diversified solutions. This prior is iteratively updated via parallel stochastic search in the spirit of Ant Colony Optimization (ACO), leading to the posterior distribution that generates near-optimal solutions. Extensive experiments across seven combinatorial optimization problems demonstrate GFACS's promising performances.

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