Author: sislam22

While nuclear weapons of mass destruction exist, thankfully they have only been used in anger twice. Therefore, there is little know about how people will react to them. As a consequence of this unknown, we synthesized a hundred years of disaster research to build a model to explore this gap in our understanding of the social effects of a nuclear weapon of mass destruction (NWMD). By reviewing disaster literature, we argue that disasters, including a NWMD, should be viewed as a complex system of three parts (i.e., the physical, social and individual). These three parts inform an agent-based model on how society might react following a nuclear weapon of mass destruction. Specifically, the agent-based model captures the main properties of complex adaptive systems such as heterogeneity, webs of connections (i.e., social networks), relationships and interactions, and adaptations arising from individual actions and decisions. Our NWMD model represents the road network and weapon effects as part of the physical environment. It also includes synthesized individuals and their social environment through agents’ social networks and emergent group dynamics after the event. This NWMD model supports the exploration of the effects of different agent behavior in times of disaster. In the base model, we characterized the response of victims of a nuclear WMD, first responders, and the rest of the population not directly impacted by the weapon. Such a model of the New York mega-city is poised to support additional studies of social effects of a nuclear WMD or disasters more generally.

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Dr. Annetta Burger, a recent graduate of the CSS program now a post-doc at NYU presented a paper based on her dissertation on complex adaptive systems as an organizing approach to understanding disasters and impacts on public health to the European Public Health Webinar on Friday, 22 October 2021 (remotely) with some assistance from with Bill Kennedy. The presentation was well received and will hopefully influence thinking about public health and disasters.

The Society for Modeling and Simulation International (SCS) awarded Hamdi Kavak, Assistant Professor, Computational and Data Sciences (CDS), the 2021 Young Simulation Scientist Award. The award recognizes scientists and engineers under the age of 35 who demonstrate excellence and leadership qualities in the field of modeling and simulation. He is the first from Mason to receive this award.

“SCS is one of the most prestigious modeling and simulation societies in the world and, at most, one Young Simulation Scientist award is given each year,” said Kavak. “I am thankful and proud to be one of the four people who have received this award since its inception.”

Kavak’s research focuses on the intersection of simulation modeling and data science and ways these connections may solve some of the greatest challenges seen in modeling. His work includes simulations and analysis of diseases, cyber warfare, population behavior, and malicious attacks against supply chain networks.

His recent summer research included a provost-funded Summer Team Impact Project and mentoring ASSIP high school and Mason college students to, according to Kavak, “understand and predict the COVID-19 pandemic from vaccine hesitancy to the emergence of new strains.”

In addition to teaching at the graduate and undergraduate level, Kavak serves as the Co-director of the Center for Social Complexity. His research support spans several organizations including the National Science Foundation, the Commonwealth Cyber Initiative, the Defense Threat Reduction Agency, and the Department of Homeland Security.

While many mathematical and statistical models in the social sciences consist of interacting agents, it is often the case that strong assumptions have to be made for reasons of analytical tractability (e.g., representative agents, rational agents, equal probability of interaction between agents, attainment of agent-level equilibrium).

Agent-based models (ABMs) are an emerging computational approach for studying social and natural phenomena in terms of interacting agents, and which facilitate the relaxation of unrealistic assumptions. Often ABMs address social phenomena about which other more conventional models exist, but direct comparisons of the output of the distinct models are not made directly or else are attempted only informally.

This workshop will focus on ABMs that reproduce the results of conventional models, and then generalize standard results by relaxing model specifications, usually in the direction of more realism. Such models agentize mathematical or econometric models and may demonstrate that conventional results are robust to certain parametric variations or are special cases of more general results.

The workshop on agentization will be held online through George Mason University, from 15-17 September, organized by the Computational Public Policy Lab and the Center for Social Complexity at Mason and sponsored by the Proteus Foundation. ABM pioneer W. Brian Arthur (Santa Fe Institute) will deliver a keynote address. We seek submissions of ABMs that closely reproduce conventional model results and then generalize them. Perhaps you have created an ABM that is similar to some standard model but which produces different results. If your ABM can be directly related to the standard model then it is of interest to this workshop. ABMs that have only notional relation to extant models are not suitable for this event.

People interested in presenting their research at this workshop should submit online by 16 August, either as a paper comparing results from an ABM to standard results, or as an abstract along with a working ABM or model output demonstrating the salience of an ABM to some existing model. It is our hope to combine a variety of papers describing agentized models from the workshop into an edited book or journal special issue. ABMs are welcome from any domain in which social processes are important. People interested in sitting in on or otherwise participating in this workshop are welcome to indicate their interest through the website. This is a free event.

We are happy to announce Dr. Hamdi Kavak as the new co-director of the Center for Social Complexity starting May 12, 2021. Since 2019, Dr. Kavak has been a faculty member of the Center and Assistant Professor at the Computational and Data Sciences Department at GMU. His research focuses on the intersection of modeling and simulation and data science. With this change, Dr. Kavak replaced the former co-director Dr. Andrew Crooks, who joined the University at Buffalo in Fall 2020. We congratulate Dr. Kavak on this new role and thank Dr. Crooks for his exceptional service.