MathModelingAgent

MathModelingAgent is a math modeling agent plugin designed to tackle open-ended mathematical modeling, prediction, optimization, estimation, simulation, and mechanism analysis, making it ideal for math modeling competitions. It addresses a critical flaw in typical LLM + Python workflows, where running code successfully or having a model that seems reasonable is often mistaken for correct conclusions. By adopting the philosophy that 'models propose, tools verify, and evidence determines conclusions,' this plugin ensures each key statement is validated as a 'claim,' providing reliable scientific backing.

Its core capability lies in the Claim-Obligation-Evidence framework: claims define statements requiring validation, obligations specify the type of evidence needed (e.g., independent recalculation, counterexamples, formal verification), and evidence is generated and recorded through tools. Only when evidence is sufficient are conclusions supported. The plugin offers two main skills: math-modeling-agent for building and advancing models, and math-modeling-audit for independently auditing existing models or papers. Tools like Python, Lean, and Wolfram are pluggable, allowing flexible workflows that degrade gracefully if tools are missing while maintaining verification integrity.

MathModelingAgent is suited for math modeling competition participants, researchers, engineers, and anyone dealing with complex mathematical problems who values rigorous validation. It not only helps generate models but also emphasizes the credibility, reproducibility, and rigor of conclusions, applicable across a wide range of scenarios from academic research to real-world problem-solving. Through strict validation and recoverable operation, MathModelingAgent aims to elevate math modeling from subjective speculation to evidence-driven scientific practice.