Abstract
Normative environments for multi-agent systems provide means to monitor and enforce agents’ compliance to their commitments. However, when the normative space is imperfect, contracts to which norms apply may be unbalanced, and agents may exploit potential flaws to their own advantage. In this paper we analyze how a normative framework endowed with a simple adaptive deterrence sanctioning model responds to different agent populations. Agents are characterized by their risk tolerance and by their social attitude. We show that risk-averse or socially concerned populations cause lesser deterrence sanctions to be imposed by the normative system.
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Lopes Cardoso, H., Oliveira, E. (2009). Risk Tolerance and Social Awareness: Adapting Deterrence Sanctions to Agent Populations. In: Lopes, L.S., Lau, N., Mariano, P., Rocha, L.M. (eds) Progress in Artificial Intelligence. EPIA 2009. Lecture Notes in Computer Science(), vol 5816. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04686-5_46
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DOI: https://doi.org/10.1007/978-3-642-04686-5_46
Publisher Name: Springer, Berlin, Heidelberg
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