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 ![]() | |
d'Avila Garcez, Artur [] | |
Genovese, Valerio [] | |
van der Torre, Leon ![]() | |
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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