Community

amoozgar Member since: Wednesday, February 01, 2012

B.S. Computer Science

AI, Agent based modeling and Social Simulation

Rocco Paolillo Member since: Monday, September 24, 2018 Full Member

BIGSSS-Departs PhD Fellow
Bremen International Graduate School of Social Sciences / Jacobs University (Germany)
PhD project: Residential Segregation and Intergenerational Immigrant Integration: A Schelling-Esser Model

Italian PhD fellow, fond of social complexity and agent-based modeling, applied to residential segregation and integration processes

Research Interests: Agent-based modeling, migrant integration, residential segregation

Cristina Chueca Del Cerro Member since: Friday, May 15, 2020

I’m a PhD researcher at the University of Glasgow working on modelling national identity polarisation on social media platforms using ABMs.

agent-based models, social networks, python, R, NetLogo

Fulco Scherjon Member since: Thursday, November 10, 2016

MSc Computer Science, Ma Archaeology

Simulation of past hominins in a realistic setting

Mamadou Diallo Member since: Monday, November 23, 2015 Full Member Reviewer

PhD Student, IT design engineer

Modeling, companion modeling, role playing games, serious games, multi-agent systems, agent-oriented simulation, complex systems, water management, artificial intelligence

Sylvie Geisendorf Member since: Friday, October 06, 2017

Dr., Prof.

Topics:

Behavioural aspects of environmental problems: Use of evolutionary approaches to investigate how people react to environmental policy.
Resource scarcity
Climate-economic Models: Understand how economic agents think and decide about climate change and climate protection
Sustainable Development

Methods:

Agent-Based-Modeling
Genetic algorithms
Evolutionary economics
Behavioural economics
Ecological economics
Complexity Theory

Forrest Stonedahl Member since: Friday, January 20, 2012 Full Member Reviewer

Masters in Computer Science at Northwestern University, PhD in Computer Science at Northwestern University

My primary research interests lie at the intersection of two fields: evolutionary computation and multi-agent systems. I am specifically interested in how evolutionary search algorithms can be used to help people understand and analyze agent-based models of complex systems (e.g., flocking birds, traffic jams, or how information diffuses across social networks). My secondary research interests broadly span the areas of artificial life, multi-agent robotics, cognitive/learning science, design of multi-agent modeling environments. I enjoy interdisciplinary research, and in pursuit of the aforementioned topics, I have been involved in application areas from archeology to zoology, from linguistics to marketing, and from urban growth patterns to materials science. I am also very interested in creative approaches to computer science and complex systems education, and have published work on the use of multi-agent simulation as a vehicle for introducing students to computer science.

It is my philosophy that theoretical research should be inspired by real-world problems, and conversely, that theoretical results should inform and enhance practice in the field. Accordingly, I view tool building as a vital practice that is complementary to theoretical and methodological research. Throughout my own work I have contributed to the research community by developing several practical software tools, including BehaviorSearch (http://www.behaviorsearch.org/)

Andrea Chareunsy Member since: Monday, January 22, 2018

PhD (Economics)

Poverty and sustainability
Development economics
Ecological economics
Agent Based Modelling
Southeast Asian economies

Arika Ligmann-Zielinska Member since: Tuesday, April 08, 2008 Full Member Reviewer

PhD

I am a spatial (GIS) agent-based modeler i.e. modeler that simulates the impact of various individual decisions on the environment. My work is mainly methodological i.e. I develop tools that make agent-based modeling (ABM) easier to do. I especially focus on developing tools that allow for evaluating various uncertainties in ABM. One of these uncertainties are the ways of quantifying agent decisions (i.e. the algorithmic representation of agent decision rules) for example to address the question of “How do the agents decide whether to grow crops or rather put land to fallow?”. One of the methods I developed focuses on representing residential developers’ risk perception for example to answer the question: “to what extent is the developer risk-taking and would be willing to build new houses targeted at high-income families (small market but big return on investment)?”. Other ABM uncertainties that I evaluate are various spatial inputs (e.g. different representations of soil erosion, different maps of environmental benefits from land conservation) and various demographics (i.e. are retired farmers more willing to put land to conservation?). The tools I develop are mostly used in (spatial) sensitivity analysis of ABM (quantitative, qualitative, and visual).

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