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Norm Internalisation in Human and Artificial Intelligence

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  • Martin Neumann

Abstract

In this article, principles of architectures relating to normative agents are evaluated with regard to the question whether and to what extend results of empirical research are incorporated in the architecture. In the human sciences, internalisation is a crucial element within the concept of norms. Internalisation distinguishes normative behaviour regulation from mere coercion. The aim of this article is to begin answering the question of to what extent normative agent architectures represent the theoretical construct of norm internalisation. The relevant research in this area may be found in socialisation research in psychology and sociology. Evaluation of conclusions from the empirical sciences allows to identify drawbacks and opportunities in existing architectures, as well as to develop suggestions for future development.

Suggested Citation

  • Martin Neumann, 2010. "Norm Internalisation in Human and Artificial Intelligence," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 13(1), pages 1-12.
  • Handle: RePEc:jas:jasssj:2008-62-4
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    References listed on IDEAS

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    1. Matthias Meyer & Iris Lorscheid & Klaus G. Troitzsch, 2009. "The Development of Social Simulation as Reflected in the First Ten Years of JASSS: a Citation and Co-Citation Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 1-12.
    2. Paul Windrum & Giorgio Fagiolo & Alessio Moneta, 2007. "Empirical Validation of Agent-Based Models: Alternatives and Prospects," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(2), pages 1-8.
    3. Chris Goldspink, 2000. "Modelling Social Systems As Complex: Towards a Social Simulation Meta-Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 3(2), pages 1-1.
    4. Olivier Barreteau & Christophe Le Page & Patrick D'aquino, 2003. "Role-Playing Games, Models and Negotiation Processes," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 6(2), pages 1-10.
    5. Rosaria Conte & Frank Dignum, 2001. "From Social Monitoring to Normative Influence," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 4(2), pages 1-7.
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    1. Макаров В.Л., 2013. "Социальное Моделирование Набирает Обороты," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 49(4), pages 5-17, октябрь.

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