selforg and swarm-references

Self-Organization and Swarm Intelligence References

Gary Fontaine, Ph.D.

Axelrod, R. (1997). The dissemination of culture: A model with local convergence and global polarization, Journal of Conflict Resolution, 41, 203-226. Reprinted in R. Axelrod (1997), The Complexity of Cooperation. Princeton, NJ: Princeton University Press.

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Blum, C. & Merkle, D. (2008). Swarm Intelligence: Introduction and Applications. Berlin: Springer.

Bonabeau, E., Dorigo, M., and Theraulaz, G. (1999). Swarm Intelligence: From Natural to Artificial Systems. New York: Oxford University Press.

Bonabeau, E. & Meyer, C. (2001). Swarm Intelligence: A Whole New Way to Think About Business. Harvard Business Review, May, 107-114.

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Camazine, S, Deneubourg, J. L., Franks, N. R., Sneyd, J., Theraulaz, G. and Bonabeau, E. (2001). Self-Organization in Biological Systems. Princeton, NJ: Princeton University Press, 143-145.

Caporael, L. (1997). The evolution of truly social cognition: The core configurations model. Personality and Social Psychology Review, 1, 276-298.

Cho, Sung-Bae (2006). Intelligent System Design for episodic Memory on Mobile Daily Life. The Sixth International conference on Intelligent system Design and Applications. Jinan, China.

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Goethals, G. R., & Darley, J. M. (l977). Social comparison theory: An attributional approach. In J. M. Suls, & R. L. Miller, Social comparisons processes: Theoretical and empirical perspectives. Washington, DC:

Festinger, L. (1954) A theory of social comparison processes, Human Relations, 7, 117-40.

Fogel, L. J. (1995). Evolutionary Computation: Toward a New Philosophy of Machine Intelligence. Piscataway, NK: IEEE Press.

Fontaine, G. (2003). The “Knowledge Paradox” in Global Management: Local versus Global Assignment Strategies. International Journal of Knowledge, Culture and Change Management, Vol. 3, 659-669. http://garyfontaine.cgpublisher.com/product/pub.28/prod.26

Fontaine, G. (2005). A Self-Organization Perspective on the Impact of Local verses Global Assignment Strategies and Knowledge Building. International Journal of Diversity in Organisations, Communities and Nations, 5(1), 57-66. http://garyfontaine.cgpublisher.com/product/pub.29/prod.183

Fontaine, G. (2006). Global Swarming. Proceedings of the Sixth International Conference on Intelligent System Design and Applications (ISDA'06), 1212-1215. www2.computer.org/portal/web/csdl/doi/10.1109/ISDA.2006.253785

Fröhlich, F (1996) Neural Networks with Java. Fachhochschule Regensburg, Department of Computer Science http://rfhs8012.fh-regensburg.de/%7Esaj39122/jfroehl/diplom/e-index.html

Gilbert, N. & Troitzsch, K. G. (2005). Simulation for the social scientist. Open University Press.

Graham, C. A. and W. C. McGrew 1980. Menstrual synchrony in female Undergraduates living on a coeducational campus. Psychoneuroendocrinology 5: 245-252. Gurney, K. (1997). An Introduction to Neural Networks. London:UCL Press. (online version at http://www.shef.ac.uk/psychology/gurney/notes/index.html.)

Grasse, P.-P. (1959). La reconstruction du nid et les coordinations inter-individuelles chez bellicositermes et cubiterms sp. La theorie de la stigmergie: Essai d'interpretation du comportement des termites constructeurs. Insect Societies, 6, 41-80.

Grimm, V. & Railsback, S. F. (2005). Individual-based modeling and ecology. Princeton, NJ: Princeton University Press.

Gurney, K. (1997). An Introduction to Neural Networks. London:UCL Press. (online version at http://www.shef.ac.uk/psychology/gurney/notes/index.html.)

Henrich, J. & Boyd, R. (1998). The evolution of conformist transmission and the emergence of between-group difference. Evolution and Human Behavior, 19, 215-242.

Holland, J. (1998). Emergence: From Chaos to Order. Reading, MA: Perseus Books.

Kauffman, S. A. (1995). At Home in the Universe: The Search for the Laws of Self-Organization and Complexity. New York: Oxford University Press.

Kennedy, J. & Eberhart, R. C. (2001). Swarm Intelligence. San Francisco: Morgan Kaufmann.

Kennedy, J. (2006). The Particle Swarm: Individual and Collective Intelligence. The Sixth International conference on Intelligent system Design and Applications. Jinan, China.

Klarreich, Erica (2006). The Mind of the Swarm. Math explains how group behavior is more than the sum of its parts. Science News (Nov. 25) 170:22, 347-349.

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Langton, C. G. (1991). Computation at the edge of chaos: Phase transitions and emergent computation. In S. Forrest (Ed.), Emergent Computation: Self-Organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks. Cambridge, MA: The MIT Press.

Latane, B. & L'Herrou, T. (1996). Spatial clustering in the conformity game: Dynamic social impact in electronic groups. Journal of Personality and Social Psychology, 70, 1218-1230.

Latane, B., Liu, J. H., Nowak, A., Bonevento, M. & Zheng, L. (1995). Distance matters: Physical space and social impact. Personality and Social Psychology Bulletin, 21, 795-805.

Lee, S., Monge, P., Bar, F. & Matei, S. A. (2007). The emergence of clusters in the global telecommunications network. Journal of Communication, 57, 415-434.

Mendes, R. & Neves, J. (2004). What makes a successful society? Experiments with population topologies in particle swarms. Advances in Artificial Intelligence: XVII Brazilian symposium on Artificial Intelligence--SBIA'04.

Mendes, R., Kennedy, J. & Neves, J. (2004). The fully informed particle swarm: Simpler, maybe better. IEEE Transactions of Evolutionary Computation, 8(3).

Michalewicz, Z., Schmidt, M., Michalewiczt, M. & Constantin, C. (2007). Adaptive Business Intelligence. Berlin: Springer.

Millonas, M. M. (1993). Swarms, phase transitions, and collective intelligence. In C. Langton (Ed.), Artificial Life III, 417-445. Reading, MA: Addison-Wesley.

Ohsawa, Yukio (2006). Chance Discovery: Data-Based Decision for systems Design. The Sixth International conference on Intelligent system Design and Applications. Jinan, China.

O'Sullivan, D. & M. Haklay (2000). Agent-based models and individualism: is the world agent-based? Environment and Planning A, 32(8), 1409–25.

Parrott, D. & Li X. (2004). A particle swarm model for tracking multiple peaks in a dynamic environment using speciation. Proceeding of the 2004 Congress on Evolutionary Computation, USA, pp. 98-103.

Peng, K. & Nisbett, R. E. (1999). Culture, dialectics, and reasoning about contradiction. American Psychologist, 54, 741-755.

Reggia, J. A., Schulz, R., Wilkinson, G. S. & Uriagereka, J. (2001). Conditions enabling the evolution of inter-agent signaling in an artificial world. MIT: Artificial Life 7, 3-32.

Riva, G., Loreti, P., Lunghi, M. Vatalaro, F. & Davide, F. (2002). Presence 2010: The emergence of ambient intelligence. In Riva, Davide & Ijsselsteijn , Being there: concepts, effects and measurements of user presence in synthetic environments. Amsterdam, the Netherlands: IOS Press. www.emergingcommunication.com/volume5.html

Rucker, R. (1999). Seek! New York: Four Walls Eight Windows.

Smith, E. R. (2008). Social relationships and groups: New insights on embodied and distributed cognition. Cognitive Systems Research, 9(1-2), 24-32

Smith, E. R. & Semin, G. R. (2004). Socially situated cognition: Cognition in its social context. Advances in Experimental Social Psychology, 36, 53-117.

Smith, L. (2001). An Introduction to Neural Networks. Centre for Cognitive and Computational Neuroscience, Department of Computing and Mathematics, University of Sterling, Scotland, UK.

Suls, L, Martin, R. & Wheeler, L. (2002). Social Comparison: Why, With Whom, and With What Effect? Current Directions in Psychological Science, 11(5), 159.

Suls, L. & Wheeler, L. (2000). Handbook of Social Comparison: Theory & Research. NY: Kluwer Academic/Plenum.

Thibault, J. W. & Kelley, H. H. (1952). The Social Psychology of Groups. New York: John Wiley & Sons.

Wolfram, S. (1994). Cellular Automata and Complexity: Collected Papers. Reading, MA: Addison-Wesley.