Displaying 10 of 391 results for "J Van Der Beek" clear search
PhD student in Economic History, Universidade de São Paulo.
My research interests are the history of Gaelic Ireland (13th and 14th centuries), historical game studies, and the use of formal modeling techniques in historical research.
Cristina Montañola Sales is an assistant professor at Institut Químic de Sarrià in Ramon Llull University, where she teaches subjects in ICT and statistics. She holds a PhD in Statistics and Operations Research and specializes in the investigation of novel quantitative methods for studying human behavior, such as agent-based models and spatio-temporal analysis. Her interdisciplinary research combines mathematics with social sciences, biomedicine and High-Performance Computing. She has studied various contexts, such as the dynamics of mobility of Gambian emigrants, demographic forecasting in South Korea, and ecological resilience of hunter-gatherers in India. Her research on tuberculosis transmissions and COVID-19 has advanced knowledge in epidemics, demographic dynamics and computational statistics. She has published articles and participated in international projects on simulation, parallel computing and global health.
validation, computer performace, epidemics, demography
My research focuses on pastoral systems. I examine how pastoralists adapt to changing ecological, political and institutional conditions that affect their lives and livelihoods. I have been conducting research with pastoralists in the Far North Region of Cameroon since 1993. The long-term research has allowed me to develop innovative, interdisciplinary research projects with colleagues at the Ohio State University and the University of Maroua in Cameroon. Check out my website for more information about my research, teaching, and other scholarly activities: http://mlab.osu.edu
Pastoral systems, management of common-pool resources, coupled human and natural systems, complex adaptive systems, regime shifts, resilience, ecology of infectious diseases, herder-farmer conflicts, pastoral development, political ecology.
Gary Polhill did a degree in Artificial Intelligence and a PhD in Neural Networks before spending 18 months in industry as a professional programmer. Since 1997 he has been working at the Institute on agent-based modelling of human-natural systems, and has worked on various international and interdisciplinary projects using agent-based modelling to study agricultural systems, lifestyles, and transitions to more sustainable ways of living. In 2016, he was elected President of the European Social Simulation Association, and was The James Hutton Institute’s 2017 Science Challenge Leader on Developing Technical and Social Innovations that Support Sustainable and Resilient Communities.
ABM applied to natural resources and reputation/colaboration.
Social network analysis has an especially long tradition in the social science. In recent years, a dramatically increased visibility of SNA, however, is owed to statistical physicists. Among many, Barabasi-Albert model (BA model) has attracted particular attention because of its mathematical properties (i.e., obeying power-law distribution) and its appearance in a diverse range of social phenomena. BA model assumes that nodes with more links (i.e., “popular nodes”) are more likely to be connected when new nodes entered a system. However, significant deviations from BA model have been reported in many social networks. Although numerous variants of BA model are developed, they still share the key assumption that nodes with more links were more likely to be connected. I think this line of research is problematic since it assumes all nodes possess the same preference and overlooks the potential impacts of agent heterogeneity on network formation. When joining a real social network, people are not only driven by instrumental calculation of connecting with the popular, but also motivated by intrinsic affection of joining the like. The impact of this mixed preferential attachment is particularly consequential on formation of social networks. I propose an integrative agent-based model of heterogeneous attachment encompassing both instrumental calculation and intrinsic similarity. Particularly, it emphasizes the way in which agent heterogeneity affects social network formation. This integrative approach can strongly advance our understanding about the formation of various networks.
Displaying 10 of 391 results for "J Van Der Beek" clear search