Amirhoshang Hoseinpour Dehkordi Member since: Friday, January 23, 2015

Master of Science, Bachelor of Science

social simulation, Multiagent Systems, Process Algebra, Game Theory

Smarzhevskiy Ivan Member since: Sunday, August 17, 2014 Full Member Reviewer

Associate professor of chair of economics and mathematical methods

decision making, agent based models

Christopher Thron Member since: Saturday, November 07, 2015

Ph.D. in physics, University of Kentucky, Ph.D. in mathematics, University of Wisconsin

Mathematical modeling and simulation in social sciences, biology, physics, and signal processing.

Eric Kameni Member since: Monday, October 19, 2015 Full Member Reviewer

Ph.D. (Computer Science) - Modelisation and Application, Institute for Computing and Information Sciences (iCIS) and Institute for Science, Innovation and Society (ISIS), Faculty of Science, Radboud University, Netherland, Master’s degree with Thesis, University of Yaounde I

Eric Kameni holds a Ph.D. in Computer Science option modeling and application from the Radboud University of Nijmegen in the Netherlands, after a Bachelor’s Degree in Computer Science in Application Development and a Diploma in Master’s degree with Thesis in Computer Science on “modeling the diffusion of trust in social networks” at the University of Yaoundé I in Cameroon. My doctoral thesis focused on developing a model-based development approach for designing ICT-based solutions to solve environmental problems (Natural Model based Design in Context (NMDC)).

The particular focus of the research is the development of a spatial and Agent-Based Model to capture the motivations underlying the decision making of the various actors towards the investments in the quality of land and institutions, or other aspects of land use change. Inductive models (GIS and statistical based) can extrapolate existing land use patterns in time but cannot include actors decisions, learning and responses to new phenomena, e.g. new crops or soil conservation techniques. Therefore, more deductive (‘theory-driven’) approaches need to be used to complement the inductive (‘data-driven’) methods for a full grip on transition processes. Agent-Based Modeling is suitable for this work, in view of the number and types of actors (farmer, sedentary and transhumant herders, gender, ethnicity, wealth, local and supra-local) involved in land use and management. NetLogo framework could be use to facilitate modeling because it portray some desirable characteristics (agent based and spatially explicit). The model develop should provide social and anthropological insights in how farmers work and learn.

emaille Member since: Friday, February 03, 2012

Ph D.

Land cover changes spatial agents based modelling
Forest fire risk modelling
Geographical information based modelling
Decision support for land planning

Roy Wilson Member since: Thursday, March 24, 2016

PhD Social and Comparative Analysis in Education, MS History and Policy, MH Humanities, MS Computer Science, MA Mathematics, BA Mathematics and Philosophy

I am interested in the study of small-group decision-making using agent-based simulation of models grounded in sociological social psychology. I am also interested in a particular kind of small-group decision-making: peer review.

Guido Fioretti Member since: Tuesday, April 24, 2012 Full Member Reviewer


Guido Fioretti, born 1964, graduated in Electronic Engineering in 1991 at La Sapienza University, Rome. In 1995, he received a PhD in Economics from this same university. Guido Fioretti is currently a lecturer of Organization Science at the University of Bologna.

I am interested in combining social with cognitive sciences in order to model decision-making facing uncertainty. I am particularly interested in connectionist models of individual and organizational decision-making.

I may make use of agent-based models, statistical network analysis, neural networks, evidence theory, cognitive maps as well as qualitative research, with no preference for any particular method. I dislike theoretical equilibrium models and empirical research based on testing obvious hypotheses.

Tika Adhikari Member since: Friday, January 20, 2012 Full Member Reviewer

Ph D, Student

Development of spatial agent-based models to sustainability science and ecosystem service assessment, integration of agent-based model with biophysical process based model, improvement of theory of GIScience and land use change science, development of spatial analytical approach (all varieties of spatial regression), spatial data modeling including data mining, linking processes such as climate change, market, and policy to study patterns.

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