Connectionism and cognitive architecture: a critical analysis
Connections and symbols
A neurocomputational perspective: the nature of mind and the structure of science
A neurocomputational perspective: the nature of mind and the structure of science
Recursive distributed representations
Artificial Intelligence - On connectionist symbol processing
The cascade-correlation learning architecture
Advances in neural information processing systems 2
Holographic Recurrent Networks
Advances in Neural Information Processing Systems 5, [NIPS Conference]
Particularism and the Classification and Reclassification of Moral Cases
IEEE Intelligent Systems
| Hi-index | 0.00 |
The purpose of this paper is to examine critically Jerry Fodor's views of the limits of computational neural network approaches to understand intelligence. Fodor distinguishes between two different approaches to computationally modelling intelligence, and while he raises problems with both, he is more concerned with the approach taken by those who make use of neural network models of intelligence or cognition. Fodor's claims regarding neural networks are found wanting, and the implications of these shortcomings for computational modelling of cognition are discussed.