publication . Conference object . 2011

How to Prevent Intolerant Agents from High Segregation?

Collard, Philippe; Mesmoudi, Salma;
English
  • Published: 08 Aug 2011
  • Publisher: HAL CCSD
  • Country: France
Abstract
International audience; In the framework of Agent-Based Complex Systems we examine dynamics that lead individuals towards spatial segregation. Such systems are constituted of numerous entities, among which local interactions create global patterns which cannot be easily related to the properties of the constituent entities. In the 70's, Thomas C. Schelling showed that an important spatial segregation phenomenon may emerge at the global level, if it is based upon local preferences. Moreover, segregation may occur, even if it does not correspond to agent preferences. In real life preferences regarding segregation are influenced by individual contexts as well as so...
Subjects
free text keywords: computational sociology, micromotives and macrobehaviour, Agent-based model, Schelling model of segregation, Complex system, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA], [SHS.SOCIO]Humanities and Social Sciences/Sociology
Related Organizations
16 references, page 1 of 2

Banos, A. (2009). Exploring network effects in schelling? segregation model. S4-MODUS workshop Multi-scale interactions between urban forms and processes.

Belton, V. and Stewart, T. (2002). Multiple Criteria Decision Analysis: An Integrated Approach. Springer-Verlag.

Brownlee, J. (2007). Satisficing, optimization, and adaptive systems. CIS Technical Report 070305A.

Carrington, W. and Troske, K. (1997). On measuring segregation in samples with small units. Journal of Business & Economic Statistics, pages 402-409.

Dyer, J., Fishburn, P., Steuer, R., Wallenius, J., and Zionts, S. (1992). Multiple criteria decision making, multiattribute utility theory the next ten years. Management Science, 38(5):645-654.

Edmonds, B. and Hales, D. (2005). Computational simulation as theoretical experiment. Journal of Mathematical Sociology, 29(3):209-232.

Gerhold, S., Glebsky, L., Schneider, C., Weiss, H., and Zimmermann, B. (2008). Computing the complexity for schelling segregation models. Nonlinear Science and Numerical Simulation, 13 (10):2236-2245.

Goffette-Nagot, F., Jensen, P., and Grauwin, S. (2009). Dynamic models of residential segregation: Brief review, analytical resolution and study of the introduction of coordination. HAL-CCSD. [OpenAIRE]

Izquierdo, L., Izquierdo, S., and Galan, J.and Santos, J. (2009). Techniques to understand computer simulations: Markov chain analysis. Journal of Artificial Societies and Social Simulation, 12(16).

Pancs, R. and Vriend, N. (2003). Schelling's spatial proximity model of segregation revisited. Computing in Economics and Finances.

Pham, D. (2004). From Agent-Based Computational Economics towards Cognitive Economics. in Bourgine P., Nadal J.P eds: Cognitive Economics: An Interdisciplinary Approach. Springer verlag.

Rosser, J. B. J. (1999). On the complexities of complex economics dynamics. Journal Of Economic Perspectives, 13:169-192.

Schelling, T. C. (1971). Dynamic models of segregation. Journal of Mathematical Sociology, 1:143-186.

Simon, H. A. (1956). Rational choice and the structure of the environment. Psychological Review, 63:129-138.

Wilensky, U. (1999). Center for connected learning and computerbased modeling. http://ccl.northwestern.edu/netlogo/.

16 references, page 1 of 2
Any information missing or wrong?Report an Issue