David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Minds and Machines 2 (1):71-83 (1992)
The importance of the Stability Problem in neurocomputing is discussed, as well as the need for the study of infinite networks. Stability must be the key ingredient in the solution of a problem by a neural network without external intervention. Infinite discrete networks seem to be the proper objects of study for a theory of neural computability which aims at characterizing problems solvable, in principle, by a neural network. Precise definitions of such problems and their solutions are given. Some consequences are explored, in particular, the neural unsolvability of the Stability Problem for neural networks.
|Keywords||Neural networks dynetic problem infinite networks neural computability neurocomputing scalability stability problem Turing machine universal neural network cellular automata|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Gail A. Carpenter (2000). Combining Distributed and Localist Computations in Real-Time Neural Networks. Behavioral and Brain Sciences 23 (4):473-474.
Enrico Blanzieri (1997). Dynamical Learning Algorithms for Neural Networks and Neural Constructivism. Behavioral and Brain Sciences 20 (4):559-559.
François Chapeau-Blondeau (1995). Information Processing in Neural Networks by Means of Controlled Dynamic Regimes. Acta Biotheoretica 43 (1-2):155-167.
Pete Mandik (2003). Varieties of Representation in Evolved and Embodied Neural Networks. Biology and Philosophy 18 (1):95-130.
R. C. Lacher (1993). Expert Networks: Paradigmatic Conflict, Technological Rapproachement. [REVIEW] Minds and Machines 3 (1):53-71.
Peter Csermely (2009). Weak Links: The Universal Key to the Stability of Networks and Complex Systems. Springer.
Adam Barrett & Harald Atmanspacher, Stability Criteria for the Contextual Emergence of Macrostates in Neural Networks.
D. C. Dennett & C. F. Westbury (1999). Stability is Not Intrinsic. Behavioral and Brain Sciences 22 (1):153-154.
Gualtiero Piccinini (2008). Some Neural Networks Compute, Others Don't. Neural Networks 21 (2-3):311-321.
Added to index2009-01-28
Total downloads6 ( #224,179 of 1,413,318 )
Recent downloads (6 months)1 ( #154,079 of 1,413,318 )
How can I increase my downloads?