InfEngine：一种用于红外辐射计算的自验证和自优化智能引擎
InfEngine: A Self-Verifying and Self-Optimizing Intelligent Engine for Infrared Radiation Computing
AI总结：
InfEngine是一种自验证和自优化的智能引擎，通过整合四个专门代理，实现红外辐射计算的自动化与优化，提升科研效率。
摘要：
红外辐射计算是气候科学、遥感和光谱学进步的基础，但仍然受到手动工作流的限制。我们介绍了InfEngine，一种自主的智能计算引擎，旨在推动从由人主导的编排向协作自动化转变。它通过两个核心创新整合了四个专门的代理：自我验证，通过联合求解器-评估器调试，提高了功能正确性和科学合理性；自我优化，通过进化算法与自发现的适应函数实现，促进了自主性能优化。在InfBench上评估了200个红外特定任务，并通过InfTools的270个精心挑选的工具进行驱动，InfEngine实现了92.7%的通过率，并比手动专家努力快21倍。更根本的是，它展示了研究人员如何从手动编码转向与自验证、自优化的计算伙伴协作。通过生成可重用、已验证和优化的代码，InfEngine将计算工作流转化为持久的科学资产，加速了科学发现的周期。代码：https://github.com/kding1225/infengine
英文摘要：
Infrared radiation computing underpins advances in climate science, remote sensing and spectroscopy but remains constrained by manual workflows. We introduce InfEngine, an autonomous intelligent computational engine designed to drive a paradigm shift from human-led orchestration to collaborative automation. It integrates four specialized agents through two core innovations: self-verification, enabled by joint solver-evaluator debugging, improves functional correctness and scientific plausibility; self-optimization, realized via evolutionary algorithms with self-discovered fitness functions, facilitates autonomous performance optimization. Evaluated on InfBench with 200 infrared-specific tasks and powered by InfTools with 270 curated tools, InfEngine achieves a 92.7% pass rate and delivers workflows 21x faster than manual expert effort. More fundamentally, it illustrates how researchers can transition from manual coding to collaborating with self-verifying, self-optimizing computational partners. By generating reusable, verified and optimized code, InfEngine transforms computational workflows into persistent scientific assets, accelerating the cycle of scientific discovery. Code: https://github.com/kding1225/infengine
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
