Abstract
A fundamental issue in the implementation of symbol-manipulation with neural networks is the unlimited productivity of symbol-production systems. Because each realistic neural network is a finite-state system [1], unlimited productivity cannot be implemented with neural networks. Therefore, the only symbol-production which seems possible with neural networks is the production of a regular (finite-state) language. This has serious consequences for the generation of cognitive behaviour with neural networks, in particular natural language processing, which requires the productivity of non-regular production systems [2]. If it is not possible to implement such production systems in neural networks, neural network theory will remain on the level of behaviourism.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
