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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Cornell University’s Hod Lipson presents “The Robotic Scientist: Automating Discovery, from Cognitive Robotics to Computational Biology” as part of the IRIM Robotics Seminar Series. The event will be held in the TSRB Auditorium from 12-1 p.m. and is open to the public.
Abstract
Can robots discover scientific laws automatically? Despite the prevalence of computing power, the process of finding natural laws and their corresponding equations has resisted automation. This talk will outline a series of recent research projects—starting with self-reflecting robotic systems and ending with machines that can formulate hypotheses, design experiments, and interpret the results—to discover new scientific laws. We will see examples from psychology to cosmology, from classical physics to modern physics, from big science to small science.
For additional information:
Schmidt M., Lipson H. (2009) “Distilling Free-Form Natural Laws from Experimental Data,” Science, Vol. 324, no. 5923, pp. 81 - 85.
Bio
Hod Lipson is an associate professor in the School of Mechanical and Aerospace Engineering and Computing and Information Science department at Cornell University in Ithaca, New York. He directs the Creative Machines Lab, which focuses on novel ways for automatic design, fabrication, and adaptation of virtual and physical machines. He has led work in areas such as evolutionary robotics, multi-material 3D printing, machine self-replication, and programmable self-assembly. Lipson received his Ph.D. from Technion – Israel Institute of Technology in 1998, and completed postdoctoral appointments at Brandeis University and MIT. His research focuses primarily on biologically inspired approaches, as they bring new ideas to engineering and new engineering insights to biology.