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2014 | Economics and Business Communication Challenges : International Week | 138--148
Tytuł artykułu

Modelling Complex Dynamics and Distributed Generation of Knowledge with Bacterial-Based Algorithms

Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This study aimed to test that connected and heterogeneous societies with peer-to-peer (P2P) exchanges are more resilient than centralized and homogeneous ones. In agent-based modeling, agents with bounded rationality interact in a common environment guided by local rules, leading to Complex Adaptive Systems that are named "artificial societies". These simplified models of human societies grow from the bottom up in computational environments and can be used as a laboratory to test some hypotheses. We have demonstrated that in a model based on free interactions among autonomous agents, optimal results emerge by incrementing diversity and decentralization of communication structures, as much as in real societies Internet is leading to the emergence of improvements in collective intelligence. In order to achieve a real "Knowledge Society", what we have named a "P2P Society", it is necessary to increase decentralization and heterogeneity through information policies, distributed communication networks, open e-learning approaches and initiatives like public domain licenses, free software and open data. (original abstract)
Twórcy
  • University of Valencia, Spain
  • Universidad Carlos III, Madrid, Spain
Bibliografia
  • Barabási A.-L. & Oltvai Z. N. (2004), Network Biology: Understanding the Cell's Functional Organization, "Nature Reviews. Genetics", 5, pp. 101-113.
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  • Bauwens M. (2005), The Political Economy of Peer Production, ctheory.net, http://www.ctheory.net/articles.aspx?id=499, retrieved on November, 23, 2008.
  • Bauwens M., Sussan R. (2005), Peer to Peer and Human Evolution, http://www.agoravox. li'/IMG/P2Pandl IumanEvolV2.pdf, retrieved on October 11,2014.
  • Cioffi-Revilla C. & Rouleau M. (2010), MASON RebeLand: An Agent-Based Model of Politics, Environment, and Insurgency, "International Studies Review", 12(1), pp. 31-52.
  • Deffuant G. & Gilbert N., eds. (2011), Viability and Resilience of Complex Systems, Heidelberg: Springer Berlin Heidelberg, Berlin.
  • Epstein J. M. & Axtell R. (1996), Growing Artificial Societies, Proceedings of the fifth annual CCSC northeastern, p. 208.
  • González Rodríguez D. (2011), Simulador de bacterias sintéticas: la conjugación como protocolo de comunicación entre células, I Jornadas Doctorales de Castilla-La Mancha (Resúmenes de Comunicaciones).
  • Heylighen F. (1989), Self-organization, Emergence and the Architecture of Complexity, Proceedings of the 1st European Conference of Complexity.
  • Lansing J. S. (2003), Complex Adaptive Systems, "Annual Review of Anthropology", 32, pp. 183-204.
  • Mitchell M. (1999), An Introduction to Genetic Algorithms, Cambridge, Massachusetts.
  • Tesfatsion L. (2003), Agent-based Computational Economics: Modeling Economies as Complex Adaptive Systems, "Information Sciences", 149(4), pp. 262-268.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171351943

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