Reference : Embedding Normative Reasoning into Neural Symbolic Systems
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/12969
Embedding Normative Reasoning into Neural Symbolic Systems
English
Boella, Guido []
Colombo Tosatto, Silvano mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
d'Avila Garcez, Artur []
Genovese, Valerio []
van der Torre, Leon mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
2011
Proceedings of the Seventh International Workshop on Neural-Symbolic Learning and Reasoning
Yes
International
7th Workshop on Neural-Symbolic Learning and Reasoning 2011, NeSy2011
July 17, 2011
[en] Normative systems are dynamic systems because
their rules can change over time.
Considering this problem, we propose a neural-
symbolic approach to provide agents the instru-
ments to reason about and learn norms in a dynamic
environment.
We propose a variant of d’Avila Garcez et al. Con-
nectionist Inductive Learning and Logic Program-
ming(CILP) System to embed Input/Output logic
normative rules into a feed-forward neural network.
The resulting system called Normative-CILP(N-
CILP) shows how neural networks can cope with
some of the underpinnings of normative reasoning:
permissions
,
dilemmas
,
exceptions
and
contrary to
duty
problems.
We have applied our approach in a simplified
RoboCup environment, using the N-CILP simula-
tor that we have developed. In the concluding part
of the paper, we provide some of the results ob-
tained in the experiments
Researchers ; Professionals ; Students ; General public ; Others
http://hdl.handle.net/10993/12969
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.369.7489&rep=rep1&type=pdf

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