Social Cognitive Maps, Swarm Collective Perception and
Distributed Search on Dynamic Landscapes
63. Vitorino Ramos,
Carlos Fernandes, Agostinho C. Rosa, Social Cognitive Maps, Swarm
Collective Perception and Distributed Search on Dynamic Landscapes,
submitted to A. Porto, A. Pazos, W. Buno (Eds.), Advancing Artificial
Intelligence through Biological Process Applications, IDEA Group Inc., 2007.
PDF file: paper (3.05 Mb)
Abstract: Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophisticated) entities interacting locally with their environment cause coherent functional global patterns to emerge. SI provides a basis with wich it is possible to explore collective (or distributed) problem solving without centralized control or the provision of a global model. To tackle the formation of a coherent social collective intelligence from individual behaviors, we discuss several concepts related to Self-Organization, Stigmergy and Social Foraging in animals. Then, in a more abstract level we suggest and stress the role played not only by the environmental media as a driving force for societal learning, as well as by positive and negative feedbacks produced by the many interactions among agents. Finally, presenting a simple model based on the above features, we will adress the collective adaptation of a social community to a cultural (environmental, contextual) or media informational dynamical landscape, represented here - for the purpose of different experiments - by several three-dimensional mathematical functions that suddenly change over time. Results indicate that the collective intelligence is able to cope and quickly adapt to unforseen situations even when over the same cooperative foraging period, the community is requested to deal with two different and contradictory purposes.
º Richárd Szabó, "Investigation of Navigating Mobile Agents in Simulation Environments", Thesis of the Doctoral Dissertation (in Hungary), Department of Software Technology and Methodology, Faculty of Informatics, Loránd Eötvös University, Budapest, 2008.
º Bailong Liu, Rubo Zhang, Changting Shi, "Analysis of Foraging Behavior in Ant Swarms based on Starlogo Simulation", in IEEE International Conference on Robotics and Biomimetics, ROBIO 07, pp. 810-815, IEEE Press, ISBN: 978-1-4244-1761-2, China, Dec. 2007.
º Robert Jaschke, Andreas Hotho, Christoph Schmitz, Bernhard Ganter, Gerd Stumme, "Discovering Shared Conceptualizations in Folksonomies", in Journal of Web Semantics, Elsevier, August 2007.
º Scheutz, M., "Real-time hierarchical swarms for rapid adaptive multi-level pattern detection and tracking", in Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 07, pp. 234-241, 2007.
º Robert Jäschke, Andreas Hotho, Christoph Schmitz and Gerd Stumme, "Analysis of the Publication Sharing Behaviour in BibSonomy", in Conceptual Structures: Knowledge Architectures for Smart Applications, LNCS, Springer, pp. 282-295, 2007.
º Luis Antón-Canalís, Elena Sánchez-Nielsen, Mario Hernández-Tejera. "Particle Swarms as Video Sequence Inhabitants For Object Tracking in Computer Vision". Sixth Internacional Conference on Intelligent System Design and Applications. Jinan, Shandong, China, Oct. 2006.
º Siphesihle M. Zuma, Matthew O. Adigun, "CACIP: a Pattern for Interfacing Components in a Context-aware Mobile Environment", in Proc. of the 17th IASTED Int. Conf. on Modelling and Simulation, pp. 416-423, Acta Press, Montreal, Canada, 2006.
º Laszlo Gulyas, Laszlo Laufer, Richard Szabo, "Measuring Stigmergy: The Case of Foraging Ants", in ESOA 06 - Fourth Int. Workshop on Engineering Self-Organizing Applications, Springer-Verlag LNCS series, Hakodate, Japan, May 2006.
º P.K. Mahanti and S. Banerjee, "Automated Testing in Software Engineering: Using Ant Colony and Self-Regulated Swarms", in R. Wamkeue (Ed.), MS 2006, Modelling and Simulation Int. Conf., ACTA Press, ISBN: 0-88986-592-2, Montreal, QC, Canada, May 2006.
º Christopher Middendorff and Matthias Scheutz, "Real-time Evolving Swarms for Rapid Pattern Detection and Tracking", in Artificial Life X - Proc. of the Tenth Int. Conf. on the Simulation and Synthesis of Living Systems, L.M. Rocha, L.S. Yaeger, M.A. Bedau, D. Floreano, R.L. Goldstone and A. Vespignani (Eds.), MIT Press, ISBN 0-262-68162-5, Bloomington, Indiana, USA, June 3-7, 2006.
º Tfaili Walid; "Optimisation Dynamique et Colonie de Fourmis", Thèse de Doctorat en Informatique (Optimisation) LiSSi, Université de Paris 12, Paris, France, 2006.
º Joaquim Castelo; "Auto-Organização em Sistemas de Sinais" (in Portuguese - MSc Thesis in Design : Self-Organization in Signalling Systems, June 06), Mestrado em Design, Faculdade de Arquitectura, Universidade Técnica de Lisboa, Lisboa, Junho 2006.
º Andries P. Engelbrecht, Fundamentals of Computational Swarm Intelligence, Wiley Science, 672 pages, Nov. 2005.
NOTE - This work was also being discussed (June 15, 2006) at LKL - LONDON KNOWLEDGE LAB, London, UK.
58. On Ants, Bacteria and Dynamic Environments.
PDF file: paper (3.05 Mb)
Abstract: Swarm Intelligence (SI) is the property of a system whereby the collective behaviors of (unsophisticated) entities interacting locally with their environment cause coherent functional global patterns to emerge. SI provides a basis with wich it is possible to explore collective (or distributed) problem solving without centralized control or the provision of a global model. To tackle the formation of a coherent social collective intelligence from individual behaviors, we discuss several concepts related to Self-Organization, Stigmergy and Social Foraging in animals. Then, in a more abstract level we suggest and stress the role played not only by the environmental media as a driving force for societal learning, as well as by positive and negative feedbacks produced by the many interactions among agents. Finally, presenting a simple model based on the above features, we will adress the collective adaptation of a social community to a cultural (environmental, contextual) or media informational dynamical landscape, represented here - for the purpose of different experiments - by several three-dimensional mathematical functions that suddenly change over time. Results indicate that the collective intelligence is able to cope and quickly adapt to unforseen situations even when over the same cooperative foraging period, the community is requested to deal with two different and contradictory purposes.
Keywords: Dynamic Optimization, Stigmergy, Swarm Intelligence and Perception, Social Cognitive Maps, Social Foraging, Self-Organization, Distributed Search and Optimization.
Cited by:º Richárd Szabó, "Investigation of Navigating Mobile Agents in Simulation Environments", Thesis of the Doctoral Dissertation (in Hungary), Department of Software Technology and Methodology, Faculty of Informatics, Loránd Eötvös University, Budapest, 2008.
º Bailong Liu, Rubo Zhang, Changting Shi, "Analysis of Foraging Behavior in Ant Swarms based on Starlogo Simulation", in IEEE International Conference on Robotics and Biomimetics, ROBIO 07, pp. 810-815, IEEE Press, ISBN: 978-1-4244-1761-2, China, Dec. 2007.
º Robert Jaschke, Andreas Hotho, Christoph Schmitz, Bernhard Ganter, Gerd Stumme, "Discovering Shared Conceptualizations in Folksonomies", in Journal of Web Semantics, Elsevier, August 2007.
º Scheutz, M., "Real-time hierarchical swarms for rapid adaptive multi-level pattern detection and tracking", in Proceedings of the 2007 IEEE Swarm Intelligence Symposium, SIS 07, pp. 234-241, 2007.
º Robert Jäschke, Andreas Hotho, Christoph Schmitz and Gerd Stumme, "Analysis of the Publication Sharing Behaviour in BibSonomy", in Conceptual Structures: Knowledge Architectures for Smart Applications, LNCS, Springer, pp. 282-295, 2007.
º Luis Antón-Canalís, Elena Sánchez-Nielsen, Mario Hernández-Tejera. "Particle Swarms as Video Sequence Inhabitants For Object Tracking in Computer Vision". Sixth Internacional Conference on Intelligent System Design and Applications. Jinan, Shandong, China, Oct. 2006.
º Siphesihle M. Zuma, Matthew O. Adigun, "CACIP: a Pattern for Interfacing Components in a Context-aware Mobile Environment", in Proc. of the 17th IASTED Int. Conf. on Modelling and Simulation, pp. 416-423, Acta Press, Montreal, Canada, 2006.
º Laszlo Gulyas, Laszlo Laufer, Richard Szabo, "Measuring Stigmergy: The Case of Foraging Ants", in ESOA 06 - Fourth Int. Workshop on Engineering Self-Organizing Applications, Springer-Verlag LNCS series, Hakodate, Japan, May 2006.
º P.K. Mahanti and S. Banerjee, "Automated Testing in Software Engineering: Using Ant Colony and Self-Regulated Swarms", in R. Wamkeue (Ed.), MS 2006, Modelling and Simulation Int. Conf., ACTA Press, ISBN: 0-88986-592-2, Montreal, QC, Canada, May 2006.
º Christopher Middendorff and Matthias Scheutz, "Real-time Evolving Swarms for Rapid Pattern Detection and Tracking", in Artificial Life X - Proc. of the Tenth Int. Conf. on the Simulation and Synthesis of Living Systems, L.M. Rocha, L.S. Yaeger, M.A. Bedau, D. Floreano, R.L. Goldstone and A. Vespignani (Eds.), MIT Press, ISBN 0-262-68162-5, Bloomington, Indiana, USA, June 3-7, 2006.
º Tfaili Walid; "Optimisation Dynamique et Colonie de Fourmis", Thèse de Doctorat en Informatique (Optimisation) LiSSi, Université de Paris 12, Paris, France, 2006.
º Joaquim Castelo; "Auto-Organização em Sistemas de Sinais" (in Portuguese - MSc Thesis in Design : Self-Organization in Signalling Systems, June 06), Mestrado em Design, Faculdade de Arquitectura, Universidade Técnica de Lisboa, Lisboa, Junho 2006.
º Andries P. Engelbrecht, Fundamentals of Computational Swarm Intelligence, Wiley Science, 672 pages, Nov. 2005.
NOTE - This work was also being discussed (June 15, 2006) at LKL - LONDON KNOWLEDGE LAB, London, UK.
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