Abstract In this paper we present an embedding of (a fragment of) Input/Output logic into feed forward Neural Networks. We make use of the neural-symbolic methodology in order to allow neural networks to reason about normative systems. By doing so we are able to exploit normative reasoning within the neural networks setting. We aim at showing how neural networks can be used to represent a knowledge base of Input/Ouput logic rules and to reason about dilemma and contrary to duty problems
