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Displaying 10 of 57 results for "Philipp S. Sommer" clear search

Roy Sanderson Member since: Mon, Jan 07, 2013 at 01:47 PM

BSc (Hons) Applied Biology Class 1, PhD

Ecological modeller; behaviour of pollinating insects (especially bumblebees) in GIS landscapes. Hope to apply ABM methods to model some of the field data we have collected

Xavier Rubio-Campillo Member since: Mon, Nov 18, 2013 at 12:49 PM

Computer Science, PhD in Heritage Studies

My interests are focused on the development of new methodologies capable of exploring the complex relations between time, space and human behavior. Simulation, game theory and spatial analysis are some of the techniques that I use to explore different research questions, from the relation between environment and culture to the evolution of warfare.
I’m also the project manager of Pandora, an open-source ABM platform specifically designed for executing large scale simulations in High-Performance Computing environments.

Jean-Philippe Aurambout Member since: Mon, Feb 10, 2014 at 07:35 PM Full Member

PhD, MS, Ing

S Johnson Member since: Thu, Oct 23, 2014 at 03:43 PM

Biological Sciences, Bioengineering

ABM modelling of molecular and cellular interactions in Lymph Nodes

Sae Schatz Member since: Tue, Nov 04, 2014 at 12:11 AM

Modeling and Simulation, Ph.D., Modeling and Simulation, M.S., Computer Information Technology, B.S.

Sae Schatz, Ph.D., is an applied human–systems researcher, professional facilitator, and cognitive scientist. Her work focuses on human–systems integration (HSI), with an emphasis on human cognition and learning, instructional technologies, adaptive systems, human performance assessment, and modeling and simulation (M&S). Frequently, her work seeks to enhance individual’s higher-order cognitive skills (i.e., the mental, emotional, and relational skills associated with “cognitive readiness”).

John Bradford Member since: Tue, Nov 04, 2014 at 08:39 PM

Ph.D. Sociology, University of Tennessee

Currently working on agent-based modeling of wealth and income distributions; formalizing some of Luhmann’s theories of communication; modeling social norms; and modeling generative mechanisms of status hierarchies.

Dehua Gao Member since: Mon, Jan 05, 2015 at 04:37 PM Full Member

**PROFESSIONS **

Associate Professor
School of Management Science and Engineering, Shandong Technology and Business University (Yantai 264005, P. R. China)

**EDUCATION BACKGROUDS **

Ph. D. Degree, 09/2009 – 07/2015
School of Economics and Management, Beihang University (P. R. China)

M. A. Degree, 09/2003 – 02/2006
The Institute of Systems Engineering, Dalian University of Technology (P. R. China)

B. A. Degree, 09/1999 – 07/2003
Department of Information and Control Engineering, Zhengzhou University of Light Industry (P. R. China)

**VISITING & SUMMER SCHOOLS **

Visiting Scholar at GECS – Research Group of Experimental and Computational Sociology (March, 2017 – February, 2018)
 Università degli Studi di Brescia (Italy)
 Co-supervisor: Professor Flaminio Squazzoni

Summer school in ‘Agent-based modeling for social scientists’ (September 4-8, 2017)
 University of Brescia, Italy
 Instructors: Flaminio Squazzoni, Simone Gabbriellini, Nicolas Payette, Federico Bianchi

The Santa Fe Institute’s Massive Open Online Course: Introduction to Agent-Based Modeling (Jun 5 – September 8, 2017)
 The Santa Fe Institute, Complexity Explore Web: abm.complexityexploer.org
 Instructors: Bill Rand

Summer school in ‘Complex systems and management’ (July 2-12, 2012)
 National Defense University, P. R. China
 Instructors: Xinjun Mao, Yongfang Liu, Dinghua Shi, Qiyue Cheng

Routine dynamics, Agent-based modeling, Computational social/organization science, Industrial systems engineering, etc.

S Mowry Member since: Wed, Feb 18, 2015 at 09:07 PM

BA Mathematics, BA Hispanic Studies

Talal Alsulaiman Member since: Fri, Feb 27, 2015 at 04:10 AM

Bachelor of Science in Systems Engineering, Master of Science in Industrial Engineering, Master of Science in Financial Engineering

In this paper, we explore the dynamic of stock prices over time by developing an agent-based market. The developed artificial market comprises of heterogeneous agents occupied with various behaviors and trading strategies. To be specific, the agents in the market may expose to overconfidence, conservatism or loss aversion biases. Additionally, they may employ fundamental, technical, adaptive (neural network) strategies or simply being arbitrary agents (zero intelligence agents). The market has property of direct interaction. The environment takes the form of network structure, namely, it takes the manifestation of scale-free network. The information will flow between the agents through the linkages that connect them. Furthermore, the tax imposed by the regulator is investigated. The model is subjected to goodness of fit to the empirical observations of the S\&P500. The fitting of the model is refined by calibrating the model parameters through heuristic approach, particularly, scatter search. Conclusively, the parameters are validated against normality, absence of correlations, volatility cluster and leverage effect using statistical tests.

Eric Kameni Member since: Mon, Oct 19, 2015 at 06:01 PM Full Member

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.

Displaying 10 of 57 results for "Philipp S. Sommer" clear search

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