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Normative Reputation and the Costs of Compliance

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Abstract

In this paper, the role of normative reputation in reducing the costs of complying with norms will be explored. In previous simulations (Conte & Castelfranchi 1995), in contrast to a traditional view of norms as means for increasing co-ordination among agents, the effects of normative and non-normative strategies in the control of aggression among agents in a common environment was confronted. Normative strategies were found to reduce aggression to a much greater extent than non-normative strategies, and also to afford the highest average strength and the lowest polarisation of strength among the agents. The present study explores the effects of the interaction between populations following different criteria for aggression control. In such a situation the normative agents alone bear the cost of norms, due to their less aggressive behaviour, while other agents benefit from their presence. Equity is then restored by raising the cost of aggression through the introduction of agents' reputation. This allows normative agents to avoid respecting the cheaters' private property, and to impose a price for transgression. The relevance of knowledge communication is then emphasised by allowing neighbour normative agents to communicate. In particular, the spreading of agents' reputation via communication allows normative agents to co-operate without deliberation at the expense of non-normative agents, thereby redistributing the costs of normative strategies.

Suggested Citation

  • Cristiano Castelfranchi & Rosaria Conte & Mario Paolucci, 1998. "Normative Reputation and the Costs of Compliance," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 1(3), pages 1-3.
  • Handle: RePEc:jas:jasssj:1997-10-1
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    File URL: http://jasss.soc.surrey.ac.uk/1/3/3/3.pdf
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    Cited by:

    1. Christopher D. Hollander & Annie S. Wu, 2011. "The Current State of Normative Agent-Based Systems," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, pages 1-6.
    2. Martin Neumann, 2008. "Homo Socionicus: a Case Study of Simulation Models of Norms," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, pages 1-6.
    3. Yutaka Nakai & Masayoshi Muto, 2008. "Emergence and Collapse of Peace with Friend Selection Strategies," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, pages 1-6.
    4. Rafael H Bordini & John A. Campbell & Renata Vieira, 1998. "Extending Ascribed Intensional Ontologies with Taxonomical Relations in Anthropological Descriptions of Multi-Agent Systems," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, pages 1-3.
    5. Nicole J. Saam & Andreas G. Harrer, 1999. "Simulating Norms, Social Inequality, and Functional Change in Artificial Societies," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, pages 1-2.
    6. Stephen Younger, 2010. "Leadership in Small Societies," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, pages 1-5.
    7. Christian Hahn & Bettina Fley & Michael Florian & Daniela Spresny & Klaus Fischer, 2007. "Social Reputation: a Mechanism for Flexible Self-Regulation of Multiagent Systems," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, pages 1-2.
    8. Francesco C. Billari & Alexia Prskawetz & Johannes F├╝rnkranz, 2002. "The cultural evolution of age-at-marriage norms," MPIDR Working Papers WP-2002-018, Max Planck Institute for Demographic Research, Rostock, Germany.

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    Keywords

    Norms; Reputation; Compliance;

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