We investigate ex ante law enforcement within a population of norm-governed learning agents using a probabilistic rule-based argumentation framework. We show that this formal framework can advantageously complete a traditional analysis based on expected utilities, in particular when hyper-rational or omniscient agents are not assumed. This has significant implications for the design of self-organising electronic institutions, where the cost of monitoring and enforcement of laws and norms has to be taken into consideration.

A Study of Ex Ante Law Enforcement in Norm-Governed Learning Agents

RIVERET, REGIS;CONTISSA, GIUSEPPE;ROTOLO, ANTONINO;SARTOR, GIOVANNI
2013

Abstract

We investigate ex ante law enforcement within a population of norm-governed learning agents using a probabilistic rule-based argumentation framework. We show that this formal framework can advantageously complete a traditional analysis based on expected utilities, in particular when hyper-rational or omniscient agents are not assumed. This has significant implications for the design of self-organising electronic institutions, where the cost of monitoring and enforcement of laws and norms has to be taken into consideration.
2013
New Frontiers in Artificial Intelligence
157
173
R. Riveret; D. Busquets; J. Pitt; G. Contissa; A. Rotolo; G. Sartor
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/305977
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