COAISep 28, 2024

Automated conjecturing in mathematics with \emph{TxGraffiti}

arXiv:2409.19379v15 citationsh-index: 2
Originality Synthesis-oriented
AI Analysis

It addresses the problem of automating mathematical conjecture generation for researchers, building incrementally on prior work like Graffiti.

The paper presents TxGraffiti, a data-driven program that automates generating conjectures in mathematics, particularly graph theory, and has contributed to numerous publications since 2017.

\emph{TxGraffiti} is a data-driven, heuristic-based computer program developed to automate the process of generating conjectures across various mathematical domains. Since its creation in 2017, \emph{TxGraffiti} has contributed to numerous mathematical publications, particularly in graph theory. In this paper, we present the design and core principles of \emph{TxGraffiti}, including its roots in the original \emph{Graffiti} program, which pioneered the automation of mathematical conjecturing. We describe the data collection process, the generation of plausible conjectures, and methods such as the \emph{Dalmatian} heuristic for filtering out redundant or transitive conjectures. Additionally, we highlight its contributions to the mathematical literature and introduce a new web-based interface that allows users to explore conjectures interactively. While we focus on graph theory, the techniques demonstrated extend to other areas of mathematics.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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