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arxiv 2408.15332 v2 pith:X6FFZMGW submitted 2024-08-27 cs.LG cs.AImath.COmath.GRmath.GT

What makes math problems hard for reinforcement learning: a case study

classification cs.LG cs.AImath.COmath.GRmath.GT
keywords conjectureproblemsseriesaddressakbulut-kirbyalgorithmicandrews-curtisbroad
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Using a long-standing conjecture from combinatorial group theory, we explore, from multiple perspectives, the challenges of finding rare instances carrying disproportionately high rewards. Based on lessons learned in the context defined by the Andrews-Curtis conjecture, we propose algorithmic enhancements and a topological hardness measure with implications for a broad class of search problems. As part of our study, we also address several open mathematical questions. Notably, we demonstrate the length reducibility of all but two presentations in the Akbulut-Kirby series (1981), and resolve various potential counterexamples in the Miller-Schupp series (1991), including three infinite subfamilies.

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