AINeutralarXiv – CS AI · 10h ago6/10
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The Two-Hump Problem: Bridging the Difficulty Gap in Mathematical Reinforcement Learning
Researchers identify a critical structural problem in reinforcement learning for mathematical search tasks, specifically the Andrews-Curtis conjecture, characterized by a 'two-hump' distribution where instances are either trivial or unsolvable. The team addresses this through novel data generation techniques, algorithmic enhancements including supermoves and Transformer architectures, and releases two large-scale benchmark datasets (AC-19 and AC-1M) to advance the field.