IC Colloquium : The Robotic Scientist: Finding invariants, from cognitive robotics to computational biology
Event details
| Date | 08.10.2012 |
| Hour | 16:15 › 17:30 |
| Speaker | Hod Lipson, Cornell University (Robotics) |
| Location | |
| Category | Conferences - Seminars |
Abstract
Can machines discover dynamical invariants automatically? From cognitive robots that create models of themselves, to automated experimental systems that look for the laws of nature, the ability to identify invariant dynamics is key. Despite the prevalence of computing power, the process of finding invariant equations has resisted automation. A key challenge to finding analytic relations automatically is defining algorithmically what makes a correlation in observed data important and insightful. By seeking dynamical invariants and symmetries, we show how we can go from finding just predictive models to finding deeper conservation laws. We demonstrated this approach by automatically searching motion-tracking data captured from various physical systems, ranging from simple harmonic oscillators to chaotic double-pendula to walking robots. Application to modeling physical and biological systems will be shown.
Biography
Hod Lipson is an Associate Professor of Mechanical & Aerospace Engineering and Computing & Information Science at Cornell University in Ithaca, NY. 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 functional rapid prototyping, machine self-replication and programmable self-assembly. Lipson received his Ph.D. from the Technion - Israel Institute of Technology in 1998, and continued to a postdoc at Brandeis University and MIT. His research focuses primarily on biologically-inspired approaches, as they bring new ideas to engineering and new engineering insights into biology.
Can machines discover dynamical invariants automatically? From cognitive robots that create models of themselves, to automated experimental systems that look for the laws of nature, the ability to identify invariant dynamics is key. Despite the prevalence of computing power, the process of finding invariant equations has resisted automation. A key challenge to finding analytic relations automatically is defining algorithmically what makes a correlation in observed data important and insightful. By seeking dynamical invariants and symmetries, we show how we can go from finding just predictive models to finding deeper conservation laws. We demonstrated this approach by automatically searching motion-tracking data captured from various physical systems, ranging from simple harmonic oscillators to chaotic double-pendula to walking robots. Application to modeling physical and biological systems will be shown.
Biography
Hod Lipson is an Associate Professor of Mechanical & Aerospace Engineering and Computing & Information Science at Cornell University in Ithaca, NY. 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 functional rapid prototyping, machine self-replication and programmable self-assembly. Lipson received his Ph.D. from the Technion - Israel Institute of Technology in 1998, and continued to a postdoc at Brandeis University and MIT. His research focuses primarily on biologically-inspired approaches, as they bring new ideas to engineering and new engineering insights into biology.
Links
Practical information
- Informed public
- Free
- This event is internal
Organizer
- Host : Prof. Christoph Koch
Contact
- Simone Muller or Christine Moscioni