Bio-inspired algorithms for collective behaviour
Monday, 09. December 2019
11:45 – 12:55
Centre for the Advanced Study of Collective Behaviour
Naomi Leonard, Princeton University, Fumin Zhang, Georgia Tech
This event is part of an event series „Seminar Series of CASCB“.
For this special CASCB seminar, we welcome two guest speakers--Naomi Leonard, Princeton, and Fumin Zhang, Georgia Tech--to present their work on the broader theme of biologically-inspired algorithms for collective behaviour. Each presentation will be slightly shorter, 30 minutes, with time for questions afterwards. Please email Jacob Davidson (firstname.lastname@example.org) if you would like to arrange a meeting with the speakers.
Naomi Leonard is an Edwin S. Wilsey Professor of Mechanical and Aerospace Engineering and associated faculty in Applied and Computational Mathematics at Princeton University. She is a MacArthur Fellow, and Fellow of the American Academy of Arts and Sciences, SIAM, IEEE, IFAC, and ASME. She received her BSE in Mechanical Engineering from Princeton University and her PhD in Electrical Engineering from the University of Maryland. Her research is in control and dynamics with application to multi-agent systems, mobile robotic sensor networks, collective animal behavior, and human decision dynamics.
Resilience and the Dynamics of Spreading Processes
Spreading processes impact biological, social, and technological systems. To systematically derive testable predictions and the means to manage spreading, models are needed that predict spreading dynamics in terms of a few parameters. We study a spreading model in which interacting agents can adjust their susceptibility to the spreading process after first exposure. The model is motivated by an investigation of regulation of foraging by desert harvester ants. Using an analytically tractable model that predicts behaviors exhibited in field data, we show how resilience of colony foraging rates to changing temperature and humidity can be explained by ants modifying their susceptibility to the spread of foraging, once exposed to outside conditions. To generalize these results, we propose and analyze a network contagion model with adjustable susceptibility and agent heterogeneity. We show how four dynamic regimes are distinguished by four numbers that depend on network structure and heterogeneity. In the bi-stable regime, not captured in traditional models, there can be a rapid cascade after a long period of quiescence. We show further how our results allow for systematic design of control strategies to suppress or promote spreading. This is joint work with Renato Pagliara (for the ant foraging study) and Deborah Gordon.
Fumin Zhang is Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. He received a PhD degree in 2004 from the University of Maryland (College Park) in Electrical Engineering, and held a postdoctoral position in Princeton University from 2004 to 2007. His research interests include mobile sensor networks, maritime robotics, control systems, and theoretical foundations for cyber-physical systems.
Bio-inspired algorithms for swarm robotics