Community

Gary Polhill Member since: Wednesday, September 05, 2012 Full Member

BA (Hons) Computing and Artificial Intelligence (Sussex), Ph. D. Guaranteeing Generalisation in Neural Networks (St. Andrews)

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.

Federico Bianchi Member since: Monday, April 14, 2014 Full Member

Ph.D., Economic Sociology and Labour Studies, University of Milan - University of Brescia (Italy), M.A., Sociology, University of Turin (Italy), B.A., Philosophy, University of Milan (Italy)

Social scientist based in Milan, Italy. Post-doctoral researcher in Sociology at the Department of Social and Political Sciences of the University of Milan (Italy), member of the Behave Lab. Adjunct professor of Social Network Analysis at the Graduate School in Social and Political Sciences of the University of Milan.

  • the link between economic exchange, solidarity, and inter-group conflict
  • peer-review evaluation in scientific publishing
  • integrating Agent-Based Modelling (ABM) with Social Network Analysis (SNA)

Lisa Gajary Member since: Saturday, March 05, 2016

Master of Arts, Doctoral Candidate in Public Affairs

As publically funded science has become increasingly complex, the policy and management literature has begun to focus more attention on how science is structured and organized. My research interests reside at the nexus of science and technology policy, organizational theory, and complexity theory—I am interested in how the management and organization of S&T research influences the implementation of policies and the emergence of organizational strategies and innovation. Although my research involves the use of multiple qualitative and quantitative methods, I rely heavily on agent based modeling and system dynamics approaches in addressing my research questions.

troukny Member since: Saturday, February 18, 2012

Civil Engineer in Computer Science

Using the Complex System science paradigm to open new ways of assessing the Systemic Risk in Financial Systems

Rodolphe Buda Member since: Monday, February 04, 2013

Doctor in Economic Science

Main Research Topics :
1) Agent-based Modeling (Communication between agents)
2) Economic and Econometric Algorithms and Software Development
3) Optimal International Trade Configuration

Alex Kara Member since: Wednesday, April 10, 2013

BA in Archaeology, Boston University, 2012

I am interested in using agent based modelling and systematic data collection to understand diachronic human-environment interactions in the Maya region of Guatemala, Mexico, and Belize.

Matteo Morini Member since: Friday, February 22, 2019 Full Member

PhD, Computer Science, ENS Lyon, MS, Economics, University of Turin

Camelia Voinea Member since: Wednesday, November 01, 2017 Full Member Reviewer

PhD

political methodology research covering agent-based modelling and simulation of political phenomena,computational models of political phenomena (political attitudes, elite, corruption, political clientelism, state capture)

Sylvie Huet Member since: Wednesday, December 19, 2018 Full Member

Researcher in social simulation or Computational social scientists
in LISC (Inrae), and associate researcher in LAPSCO (UCA) https://www.lapsco.fr/HUET-Sylvie.html

Simon Johanning Member since: Monday, July 17, 2017

BMus Composition & Music Technology, MA DDC: Music Technology

IRPact - An integrated agent based modeling approach in innovation diffusion

Goal: The goal of IRPact is to develop a flexible and generic innovation-diffusion ABM (agent-based modelling) framework, based on requirements derived from a literature analysis. The aim of IRPact is to allow for modeling a large number of application contexts and questions of interest.
It provides a formal model (framework) as well as a software implementation in order to assist modelers with a basic infrastructure for their own research.
Conceptually it is thought to be part of the IRPsim (https://irpsim.uni-leipzig.de), with the vision to bring together rational approaches and cognitive modeling in an integrated approach within the context of sustainable energy markets.

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