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Resilient MachinesJosh Bongard Intelligent robots must be able to not only adapt an existing behavior on the fly in the face of environmental perturbation, but must also be able to generate new, compensating behavior after severe, unanticipated change such as body damage. In this talk I will describe a physical robot with this latter capability, a capability we refer to as resiliency. The robot achieves this by (1) creating an approximate simulation of itself; (2) optimizing a controller using this simulator; (3) using the controller in reality; (4) experiencing body damage; (5) indirectly inferring the damage and updating the simulator; (6) re-optimizing a new controller in the altered simulator; and (6) executing this compensatory controller in reality. I will also describe recent work generalizing this approach to robot teams. Josh Bongard received his Bachelors degree in Computer Science from McMaster University, Canada, his Masters degree from the University of Sussex, UK, and his PhD from the University of Zurich, Switzerland. He served as a postdoctoral associate under Hod Lipson in the Computational Synthesis Laboratory at Cornell University from 2003 to 2006. He is the co-author of the popular science book entitled "How the Body Shapes the Way We Think: A New View of Intelligence," MIT Press, November 2006 (with Rolf Pfeifer). Currently, he is an assistant professor in the Computer Science Department at the University of Vermont. His research interests include embodied cognition and evolutionary computation, and he was named both a Microsoft Research New Faculty Fellow in 2006, as well as a member of the TR35: MIT Technology Review?s top 35 innovators under the age of 35.  |