Neural-symbolic systems are hybrid systems that integrate symbolic logic and neural networks. The goal of neural-symbolic integration is to benefit from the combination of feature...
Machine Learning systems are often distinguished according to the kind of representation they use, which can be either propositional or first-order logic. The framework working wi...
Teresa Maria Altomare Basile, Floriana Esposito, N...
Abstract. Both in classical logic and in Answer Set Programming, inconsistency is characterized by non existence of a model. Whereas every formula is a theorem for inconsistent set...
We give a notation and a logical calculus for the description and deductive manipulation of dynamic networks of communicating components. We represent such nets by hierarchical sys...
This paper studies a logical framework for automated negotiation between two agents. We suppose an agent who has a knowledge base represented by a logic program. Then, we introduc...