David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Acta Biotheoretica 42 (2-3) (1994)
Random simulation of complex dynamical systems is generally used in order to obtain information about their asymptotic behaviour (i.e., when time or size of the system tends towards infinity). A fortunate and welcome circumstance in most of the systems studied by physicists, biologists, and economists is the existence of an invariant measure in the state space allowing determination of the frequency with which observation of asymptotic states is possible. Regions found between contour lines of the surface density of this invariant measure are called confiners. An example of such confiners is given for a formal neural network capable of learning. Finally, an application of this methodology is proposed in studying dependency of the network's invariant measure with regard to: 1) the mode of neurone updating (parallel or sequential), and 2) boundary conditions of the network (searching for phase transitions).
|Keywords||No keywords specified (fix it)|
|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
B. Doyon, B. Cessac, M. Quoy & M. Samuelides (1994). On Bifurcations and Chaos in Random Neural Networks. Acta Biotheoretica 42 (2-3).
Christophe Malaterre (2009). Are Self-Organizing Biochemical Networks Emergent? In Maryvonne Gérin & Marie-Christine Maurel (eds.), Origins of Life: Self-Organization and/or Biological Evolution? EDP Sciences. 117--123.
Shaun Gallagher (2007). Simulation Trouble. Social Neuroscience 2 (3-4):353â365.
François Chapeau-Blondeau (1995). Information Processing in Neural Networks by Means of Controlled Dynamic Regimes. Acta Biotheoretica 43 (1-2).
Enrico Blanzieri (1997). Dynamical Learning Algorithms for Neural Networks and Neural Constructivism. Behavioral and Brain Sciences 20 (4):559-559.
Stan Franklin & Max Garzon (1992). On Stability and Solvability (or, When Does a Neural Network Solve a Problem?). Minds and Machines 2 (1):71-83.
J. McKenzie Alexander (2003). Random Boolean Networks and Evolutionary Game Theory. Philosophy of Science 70 (5):1289-1304.
Jacques Demongeot, Adrien Elena & Sylvain Sené (forthcoming). Robustness in Regulatory Networks: A Multi-Disciplinary Approach. Acta Biotheoretica.
Gualtiero Piccinini (2008). Some Neural Networks Compute, Others Don't. Neural Networks 21 (2-3):311-321.
Added to index2009-01-28
Total downloads4 ( #255,916 of 1,101,740 )
Recent downloads (6 months)3 ( #116,934 of 1,101,740 )
How can I increase my downloads?