From Network Connectivity Structure to Emergence of Social Norms

Babak Heydari
School of Systems and Enterprises, Stevens Institute of Technology, USA

Abstract

Computational social sciences is an interdisciplinary emerging field that cuts across several disciplines such as computer science, sociology, physics, economics and behavioral sciences. Emergence and dynamics of community structure in complex networks is one of the pillars of this new field. Design and policy decisions for many socio-technical, organizational and economic systems involve determining the connectivity structure that maximizes the utility of individual agents or that of the system as a whole. To do that, we need to develop theoretical and computational frameworks for deciding about connectivity structure in Heterogeneous Complex Networked Systems (HCNS). In this talk, we will look at question of optimal connectivity structure under two different schemes: The central scheme, where the efficient structure” is decided by a central planner, and the autonomous scheme, where stable structures emerge at the equilibrium when agents have discretion in establishing and removing links to maximize their individual pay-offs. These will be then used to determine the system-level characteristics of stable and efficient structures and to study the trade-offs between these two schemes. The talk will give an overview of our research efforts on three tracks, related to this topic: The first track is Establishing methods to determine efficient and stable structures for HCNS using analytical solutions based on strategic network formation methods, for low heterogeneity systems, as well as Agent-Based Modeling and Simulation, for arbitrary levels of heterogeneity. The other track is determining common structural characteristics of these networks as a function of systems heterogeneity, with a special emphasis on network modularity, demonstrated by our research as the key system-level parameter that varies with overall heterogeneity. Finally, we will look at the structural parameters that affect the overall behavior system through collective norms, by focusing on emergence of cooperation as a function of network structure.

Short Bio
Babak Heydari is an assistant professor at the School of Systems and Enterprises, at Stevens Institute of Technology. He holds a PhD in Electrical Engineering from University of California at Berkeley with a minor in management and economics and has three years of industry experience in Silicon Valley. Dr. Heydari has a diverse set of research interests and academic backgrounds and does interdisciplinary research at the intersection of engineering, economics and systems sciences. His current research, is on developing model-driven approach in analysis, design and governance of complex Networked systems. His research interests are network resource sharing formation and diffusion of collective behavior, modularity, emergence and evolution of collective behavior and the co-evolution of structure and behavior in complex networks. More information about his research activities, can be found on the website of his lab, Complex Evolving Networked Systems (CENS lab) at www.stevens.edu/cens.

Time: 15:00-16:00, Wednesday 28th of Mordad, 1394
Place: Kharazmi Hall, Level 4, Department of Computer Engineering,
Sharif University of Technology