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.
Part of this work has been carried out in the scope of the EC co-funded project SMART (FP7-287583). This work is partially supported by the EU Marie Curie Intra-European Fellowship 274057.
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Riveret, R., Busquets, D., Pitt, J., Contissa, G., Rotolo, A., Sartor, G. (2013). A Study of Ex Ante Law Enforcement in Norm-Governed Learning Agents. In: Motomura, Y., Butler, A., Bekki, D. (eds) New Frontiers in Artificial Intelligence. JSAI-isAI 2012. Lecture Notes in Computer Science(), vol 7856. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39931-2_12
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DOI: https://doi.org/10.1007/978-3-642-39931-2_12
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