Mathematics for and by human cognition: A resource-rational search for bottlenecks in problem-solving
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Abstract (arXiv)
Human cognitive constraints are generally viewed as limiting factors in problem-solving. We argue that these constraints can instead play a critical role in driving advances in mathematics and beyond. We propose a theory of mathematical abstraction as a resource-rational search for bottlenecks in problem-solving. Bottlenecks arising from cognitive constraints create pressure to restructure existing knowledge, potentially giving rise to novel formalisms with applications beyond the problems that originally motivated them. Drawing on episodes from the history of mathematics, we illustrate how such bottlenecks can drive the development of novel abstractions and examine how cognitive constraints and affective responses shape this process. Finally, we discuss the implications of this account for machine mathematical discovery and argue that incorporating human-like constraints may facilitate the discovery of useful mathematical abstractions.
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References · 8
- 2025AlphaEvolve: A coding agent for scientific and algorithmic discoverycited by 763
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- 2023Take a Step Back: Evoking Reasoning via Abstraction in Large Language Modelscited by 157
- 2024Compression Represents Intelligence Linearlycited by 56
- 2024ReGAL: Refactoring Programs to Discover Generalizable Abstractionscited by 32
- 2025RLAD: Training LLMs to Discover Abstractions for Solving Reasoning Problemscited by 21
- 2026Nothing from Something: Can a Language Model Discover 0?cited by 1
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