Add to ORKGIn this study, we show the specific and complementary attributes of Artificial Intelligence (AI) and of Connectionism (C). AI seems to be more adapted to modeling upper levels of data and knowledge processing performed by the brain, whereas C is more generally linked to sensory perception, reflexes or pattern recognition processes. A certain number of medical diagnosis aiding systems, combining these two paradigms, document the thesis that hybrid symbolic-connectionist architectures offer a very promising opening for the realization of complex, high level decision making systems in the years to come
In order to integrate connectionist models and symbolic AI techniques, knowledge must be represented...
Connectionism (also known as parallel distributed processing) has generated a great deal of interest...
Abstract. In this paper, we first present and compare existing categorization schemes for neuro-symb...
In this paper neural networks are used as associative memories to build an expert system for aiding ...
Intelligent systems based on first-order logic on the one hand, and on artificial neural networks (a...
The differences between connectionism and symbolicism in artificial intelligence (AI) are illustrate...
International audienceThe so called classical artificial intelligence has always dealt with those hi...
In this thesis, we discuss different techniques to bridge the gap between two different approaches t...
AbstractMore and more applications of artificial intelligence technologies are made in biomedical so...
Connectionism as a model of the mind has recently been challenging the Classical model, in which the...
Modeling higher order cognitive processes like human decision making come in three representational ...
Introduction All existing intelligent systems share a similar biological and evolutionary heritage....
This paper introduces symbolic Al and connectionism in general, and clarifies their pros and cons. B...
Connectionism as a model of the mind has recently been challenging the Classical model, in which the...
Hybrid connectionist symbolic systems have been the subject of much recent research in AI. By focusi...
In order to integrate connectionist models and symbolic AI techniques, knowledge must be represented...
Connectionism (also known as parallel distributed processing) has generated a great deal of interest...
Abstract. In this paper, we first present and compare existing categorization schemes for neuro-symb...
In this paper neural networks are used as associative memories to build an expert system for aiding ...
Intelligent systems based on first-order logic on the one hand, and on artificial neural networks (a...
The differences between connectionism and symbolicism in artificial intelligence (AI) are illustrate...
International audienceThe so called classical artificial intelligence has always dealt with those hi...
In this thesis, we discuss different techniques to bridge the gap between two different approaches t...
AbstractMore and more applications of artificial intelligence technologies are made in biomedical so...
Connectionism as a model of the mind has recently been challenging the Classical model, in which the...
Modeling higher order cognitive processes like human decision making come in three representational ...
Introduction All existing intelligent systems share a similar biological and evolutionary heritage....
This paper introduces symbolic Al and connectionism in general, and clarifies their pros and cons. B...
Connectionism as a model of the mind has recently been challenging the Classical model, in which the...
Hybrid connectionist symbolic systems have been the subject of much recent research in AI. By focusi...
In order to integrate connectionist models and symbolic AI techniques, knowledge must be represented...
Connectionism (also known as parallel distributed processing) has generated a great deal of interest...
Abstract. In this paper, we first present and compare existing categorization schemes for neuro-symb...