In this short paper we report about a "concept-wise" multipreference semantics for weighted conditionals and its use to provide a logical interpretation to some neural network models, Self-Organising Maps (SOMs) and Multilayer Perceptrons (MLPs). For MLPs, a deep network can be regarded as a conditional knowledge base, in which the synaptic connections correspond to weighted conditionals
We define a notion of reasoning using world-rank-functions, independently of any symbolic language. ...
Category theory can be applied to mathematically model the semantics of cognitive neural systems. We...
The impact of Deep Learning is due to the ability of its algorithm to mimic purely instinctive decis...
In this short paper we report about a "concept-wise" multipreference semantics for weighted conditio...
In this paper we investigate the relationships between a multipreferential semantics for defeasible ...
Weighted knowledge bases for description logics with typicality have been recently considered under ...
In this paper we report about the relationships between a multi-preferential semantics for defeasibl...
In this extended abstract we report some results concerning the relationships between a multiprefere...
Weighted knowledge bases for description logics with typicality have been recently considered under ...
Motivation: Though neural networks are extensively used to tackle the problems associated with bioin...
Hölldobler and Kalinke showed how, given a propositional logic program P, a 3-layer feedforward arti...
The paper investigates the properties of a fuzzy logic of typicality. The extension of fuzzy logic w...
We define a model-theoretic reasoning formal-ism that is naturally implemented on sym-metric neural ...
There is a gap between two different modes of computation: the symbolic mode and the subsymbolic (ne...
In this paper we establish a link between fuzzy and preferential semantics for description logics an...
We define a notion of reasoning using world-rank-functions, independently of any symbolic language. ...
Category theory can be applied to mathematically model the semantics of cognitive neural systems. We...
The impact of Deep Learning is due to the ability of its algorithm to mimic purely instinctive decis...
In this short paper we report about a "concept-wise" multipreference semantics for weighted conditio...
In this paper we investigate the relationships between a multipreferential semantics for defeasible ...
Weighted knowledge bases for description logics with typicality have been recently considered under ...
In this paper we report about the relationships between a multi-preferential semantics for defeasibl...
In this extended abstract we report some results concerning the relationships between a multiprefere...
Weighted knowledge bases for description logics with typicality have been recently considered under ...
Motivation: Though neural networks are extensively used to tackle the problems associated with bioin...
Hölldobler and Kalinke showed how, given a propositional logic program P, a 3-layer feedforward arti...
The paper investigates the properties of a fuzzy logic of typicality. The extension of fuzzy logic w...
We define a model-theoretic reasoning formal-ism that is naturally implemented on sym-metric neural ...
There is a gap between two different modes of computation: the symbolic mode and the subsymbolic (ne...
In this paper we establish a link between fuzzy and preferential semantics for description logics an...
We define a notion of reasoning using world-rank-functions, independently of any symbolic language. ...
Category theory can be applied to mathematically model the semantics of cognitive neural systems. We...
The impact of Deep Learning is due to the ability of its algorithm to mimic purely instinctive decis...
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