Collective computation in nonlinear networks and the grammar of evolvabilityProfessor Jean-Jacques Slotine AbstractComputation, synchronization, and control are key issues in complex networks. Vast nonlinear networks are encountered in biology, for instance, and in neuroscience, where for most tasks the human brain grossly outperforms engineered algorithms using computational elements 7 orders of magnitude slower than their artificial counterparts. We show that nonlinear systems tools, such as contraction analysis and virtual dynamical systems, yield simple but highly non-intuitive insights about such issues, and that they also suggest systematic mechanisms to build progressively more refined networks and novel algorithms through stable accumulation of functional building blocks and motifs. BiographyJean-Jacques Slotine was born in Paris in 1959, and received his Ph.D. from the Massachusetts Institute of Technology in 1983. After working at Bell Labs in the computer research department, in 1984 he joined the faculty at MIT, where he is now Professor of Mechanical Engineering and Information Sciences, Professor of Brain and Cognitive Sciences, and Director of the Nonlinear Systems Laboratory. He is the co-author of the textbooks “Robot Analysis and Control” (Wiley, 1986) and “Applied Nonlinear Control” (Prentice-Hall, 1991). Prof. Slotine was a member of the French National Science Council from 1997 to 2002, and of Singapore's A*STAR SigN Advisory Board from 2007 to 2010. He is currently on the Scientific Advisory Board of the Italian Institute of Technology. |