We show that by introducing an appropriate schema concept and exploiting the higher-level
features of a resonance function in a neural network it is possible to define a form of …

In this paper we will show that certain networks called 'inhibition nets' may be regarded as
cognitive agents drawing nonmonotonic inferences. It will be proven that the system CL …

There is a gap between two different modes of computation: the symbolic mode and the
subsymbolic (neuron-like) mode. The aim of this paper is to overcome this gap by viewing …

This paper is a sequel to Leitgeb7. We show that certain networks called'inhibition nets' may
be regarded as mechanisms drawing nonmonotonic inferences if only an interpretation of …

The paper consists of two parts. The first part describes a class of networks called inference
networks. An inference network is a directed graph with'primitive','OR','AND'and'NOT'nodes.' …

This paper establishes the equivalence between multilayer feedforward networks and linear
combinations of Lukasiewicz propositions. In this sense, multilayer forward networks have a …

In this paper, we introduce Artificial Nonmonotonic Neural Networks (ANNNs), a kind of
hybrid learning systems that are capable of nonmonotonic reasoning. Nonmonotonic …

We define a notion of reasoning using world-rank-functions, independently of any symbolic
language. We then show that every symmetric neural network (like Hopfield networks or …

We propose a method of doing logic programming on a Hopfield neural network.
Optimization of logical consistency is carried out by the network after the connection …

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