Gravity-Bench-v1: A Benchmark on Gravitational Physics Discovery for Agents
Koblischke, Nolan, Jang, Hyunseok, Menou, Kristen, Ali-Dib, Mohamad
–arXiv.org Artificial Intelligence
Modern science emerged from reasoning over repeatedly-observed planetary motions. We present Gravity-Bench-v1, an environment-based benchmark that challenges AI agents on tasks that parallel this historical development. Gravity-Bench-v1 evaluates agents on the discovery of physics concealed within a dynamic environment, using rigorous gravitational dynamics simulations. Gravity-Bench includes out-of-distribution cases, i.e. with physics that deviates from the real world, to evaluate true scientific generalization capabilities. Agents must plan to collect data within an experimental budget and must perform a dynamic form of data analysis and reasoning to solve tasks efficiently. Our benchmark admits an open-ended space of solutions. PhD-level solutions for each task are provided, to calibrate AI performance against human expertise. Technically at an upper-undergraduate level, our benchmark proves challenging to baseline AI agents. Gravity-Bench-v1 and planned extensions should help map out AI progress towards scientific discovery capabilities.
arXiv.org Artificial Intelligence
Jan-30-2025
- Country:
- Europe > Monaco (0.04)
- North America > Canada
- Asia > Middle East
- UAE > Abu Dhabi Emirate > Abu Dhabi (0.04)
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- Research Report (1.00)
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