Robot brain deduces physical laws
3rd Quarter 2009
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A robotic breakthrough may aid the discovery of new scientific truths that have until now eluded detection.
Reporting in the 3 April, 2009, issue of Science, Cornell University Mechanical Engineering professor, Hod Lipson, and his doctoral student, Michael Schmidt, report that their algorithm can distill fundamental natural laws from mere observations of a swinging double pendulum and other simple systems.
Without any prior instruction about the laws of physics, geometry or kinematics, the algorithm driving the computer’s number crunching was able to determine that the swinging, bouncing and oscillating of the devices arose from specific fundamental processes.
The algorithm deciphered in hours the same Laws of Motion and other properties that took Isaac Newton and his successors centuries to realise.
The new breakthrough is not far removed from Lipson’s earlier NSF CAREER award work to develop Starfish, a robot with a 'self-image' that could repair itself when damaged.
Beyond self
Lipson and Schmidt realised that if a robot can create dynamical models from data about itself, why not attempt to model the surrounding world as well?
When Lipson and Schmidt experimented with that approach, they learned their algorithm was re-discovering laws that were well known to scientists and engineers, suggesting the algorithm should be able to help uncover new laws for data sets that are less well understood.
Biological fundamentals
Lipson and Schmidt plan to use the new approach for biological systems. Biology is notoriously complicated to model, and finding fundamental laws for such systems can be difficult. With the new algorithm, the enormous data sets researchers collect about biological systems may yield invariants, unchanging aspects that may reveal underlying fundamental laws.
For more information contact Hod Lipson, Cornell University, +1 (607) 255 1686, [email protected], www.cornell.edu
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