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You are in Geoinformatics Creative Commons Resources :: Spatio-Temporal Information for Society :: Classes 2013

Spatio-Temporal Information for Society: Classes 2013

Software Description

The models described in this course will be developed using TerraME. TerraME is an extension of the Lua language. Some useful documents about TerraME:

Students should read the TerraME EMS paper first, to get a sense of the language. Then they should read the Lua papers, to learn about programming in Lua.


Classes

Ref Topic Models Exercise
1 Introduction
Lua for TerraME Lua Examples Exercise 01 - Lua Programs
Water Flows in Mono Lake Mono Lake Code in TerraME Mono Lake Case
2 Theoretical basis
Cellular Automata Cellular Automata Examples Exercise 02 - Cellular Automata
Agent-based modelling Segregation Class Exercise Ex 03 - Butterfly Model Ex 04 - Barros City Models
3 Societal modelling
Sugarscape Code Sugarscape Exercise Sugarscape
Game Theory Prisioner's Dilemma Variations on Prisioner's Dilemma
Evolution of Cooperation Code Evolution of Cooperation Cooperation Models
4 Land Change
A Case Study: Land Change in Amazonia
Building a Land Change Database Deforestation data
Land Change Modelling Databases, Scripts Deforestation Model + Scripts


Papers for Final Projects

The final project consists of an implementation and discussion of an ABM model. Each of the references below contains a description of a model.

Friedrich Muller Sex, Culture and Conflict in SugarScape. From J Epstein, R. Axtell, Growing Artificial Societies: Social Science from the Bottom Up. MIT Press, 1996.
Trade in SugarScape. From J Epstein, R. Axtell, Growing Artificial Societies: Social Science from the Bottom Up. MIT Press, 1996.
S Bergin (2012). Torsten Hägerstrand’s Spatial Innovation Diffusion Model. Available in CoMSES Computational Model Library.
Oraib Almegdadi S Heckbert (2013). MayaSim: An agent-based model of the ancient Maya social-ecological system. Available in CoMSES Computational Model Library.
R Axelrod (1997). “The dissemination of culture - A model with local convergence and global polarization.” Journal of Conflict Resolution 41: 203-226.Replicated in CoMSES Computational Model Library.
Ahmed Hussein J Pepper and B Smuts (2000). The evolution of cooperation in an ecological context: an agent-based model. Replicated in CoMSES Computational Model Library.
K Kahn (2013) A model of the Spanish Flu Pandemic. Available in CoMSES Computational Model Library.
Jan Alexander Wirwahn Schindler J (2012) A simple Multi-Agent System of the Tragedy Of the Commons. Available in CoMSES Computational Model Library.
Danielly Freire A K Knittel, R Riolo and R Snow (2011). Development and evaluation of an agent-based model of sexual partnership. Adaptive Behavior (available at CoMSES Computational Model Library.
Florian Lahn M Janssen and N.D. Rollins (2012). Evolution of cooperation in asymmetric commons dilemmas. Journal of Economic Behavior and Organization, 81: 220-229. Available in CoMSES Computational Model Library).
Sabine Schmidt Axtell, Epstein, et al. (2002) Population Growth and Collapse in a Multi-Agent Model of the Kayenta Anasazi in Long House Valley. PNAS 99(3): 7275-7279. Replicated in M Janssen and available in CoMSES Computational Model Library.
Jana Klemp S Bandini, F Celada, S Manzoni, G Vizzari (2007). Modelling the immune system: the case of situated cellular agents, Natural Computing, 6(1):19-32.
Meng Lu H. Balzter, P. W. Braun, W. Köhler (1998) Cellular automata models for vegetation dynamics. Ecological Modelling 107(2-3):113-125
Stephanie Walter S. G. Berjak, J. W. Hearne (2002) An improved cellular automaton model for simulating fire in a spatially heterogeneous Savanna system. Ecological Modelling 148(2):133–15
Nanki Sidhu S. Yassemi, S. Dragićevića, M. Schmidt(2008), Design and implementation of an integrated GIS-based cellular automata model to characterize forest fire behaviour , Ecological Modelling, 210(1–2), 71–84
Dominik Schlarmann G.Ch Sirakoulis, I. Karafyllidis, A. Thanailakis (2000) A cellular automaton model for the effects of population movement and vaccination on epidemic propagation. Ecological Modelling 133(3): 209–223
Purnima Dasgupta S. Hoya White, A. Martín del Rey, G. Rodríguez Sánchez(2007), Modeling epidemics using cellular automata. Applied Mathematics and Computation, 186(1):193-202
Christophen Stephens, Rajchandar Padmanaban C. Beauchemin, J. Samuel, J. Tuszynskia (2005) A simple cellular automaton model for influenza A viral infections. Journal of Theoretical Biology 232(2) 223–234
Markus Konkol Medeiros, L. C., Castilho, C. A. R., Braga, C., de Souza, W. V., Regis, L., Monteiro, A. M. V. (2011). Modeling the dynamic transmission of dengue fever: investigating disease persistence. PLOS neglected tropical diseases, 5(1), e942.
Saqib Rasheed R. Toivonen, J. Onnela, J. Saramaki, J. Hyvonen, K. Kaski (2006) A model for social networks. Physica A: Statistical Mechanics and its Applications 371(2):851–860
Prateek Budhwar Sławomir Nikiel (2012) Game logic simulation based on Cellular automata and flocking techniques
Tobias Tresselt F. Feitosa, A.M. Monteiro, Urban Conventions and Residential Location Choice. CAMUSS Conference (Cellular Automata Modeling forUrban and Spatial Systems 2012)
st-society-classes2013.txt · Last modified: 2014/12/01 06:59 by gilberto

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