CAM Colloquium: Naomi Ehrich Leonard (Princeton) - Nonlinear dynamics of agreement and disagreement decision making

Description

Abstract: I will present a framework for systematic investigation of multi-agent, multi-option decision making represented as continuous-time transitions in the real-valued state (agent opinions) of a nonlinear dynamical system, driven by time-varying inputs and parameters (features of agents, communication, options, and context). In the unbiased setting, where agents and options are indistinguishable, equivariant bifurcation theory predicts that all the likely state transitions (bifurcation branches) correspond to agreement and disagreement solutions, and these can be determined as a function of number of agents and number of options. When there are biases, state transitions are described by the unfolding of bifurcations. Motivated by models of neuronal networks, we define decision-making dynamics that realize the predicted state transitions as a small number of key parameters vary. We analyze the influence on decision making of system features, such as communication network topology and distribution of bias. We show further how active control of key parameters enhances the sensitivity to input and robustness to noise of the multi-agent agreement and disagreement decision-making dynamics. Bio: Naomi Ehrich Leonard is 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.