From the 1 of 7 linked papers with an AI index.
3 citations · 3 across the 7 of their papers we have counts for
7 papers
A Census of New Snake-in-the-Box Records
Paul Orland, Lucas Fagan, Michele Tarquini +7
The paper presents new longest induced (chordless) paths, called snakes, in hypercube graphs for dimensions 9 through 13, thereby improving the known lower bounds for the snake-in-…
Strings from Almost Nothing
Clifford Cheung, Grant N. Remmen, Francesco Sciotti +1
We argue that string theory emerges inevitably from a few simple assumptions about physical scattering. Consistency alone requires that all tree-level four-point scattering amplitu…
Hierarchical Reinforcement Learning for Sparse-Reward Search in Commutative Algebra
Giorgi Butbaia, Paul Orland, Coco Huang +7
Applying machine learning techniques to solving long-standing mathematical conjectures can be particularly challenging due to their extreme reward sparsity. As an illustrative exam…
The Two-Hump Problem: Bridging the Difficulty Gap in Mathematical Reinforcement Learning
Lucas Fagan, Michele Tarquini, Ali Shehper +6
Mathematical search problems present a unique challenge for Reinforcement Learning (RL) due to vast search spaces and sparse rewards. In previous works, the Andrews-Curtis (AC) con…
The Equivalence Principle at High Energies Completes the Spectrum
Francesco Calisto, Clifford Cheung, Grant N. Remmen +2
We prove a version of the completeness hypothesis that follows from the coexistence of symmetry and gravity: tree-level gravitational scattering mandates single-particle states in…
Completeness from Gravitational Scattering
Francesco Calisto, Clifford Cheung, Grant N. Remmen +2
We prove that symmetry in the presence of gravity implies a version of the completeness hypothesis. For a broad class of theories, we demonstrate that the existence of finitely man…