Reference : Neural Symbolic Architecture for Normative Agents
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Neural Symbolic Architecture for Normative Agents
Boella, Guido []
Colombo Tosatto, Silvano mailto []
d'Avila Garcez, Artur []
Genovese, Valerio []
Ienco, Dino []
van der Torre, Leon mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
In Proceedings of The Seventh International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011). May, 2011
0-9826571-7-X 978-0-9826571-7-1
Artificial Agents and Multi-Agents Systems 2011
May 2-6 2011
[en] neural-symbolic architecture ; multi-agent systems
[en] In this paper we propose a neural-symbolic architecture to represent and reason with norms in multi-agent systems. On the one hand, the architecture contains a symbolic knowledge base to represent norms and on the other hand it contains a neural network to reason with norms. The interaction between the symbolic knowledge and the neural network is used to learn norms. We describe how to handle normative reasoning issues like contrary to duties, dilemmas and exceptions by using a priority-based ordering between the norms in a neural-symbolic architecture.
Researchers ; Professionals ; Students ; General public ; Others

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