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Random Networks of Automata: A Simple Annealed Approximation
Open accessAbstract
Kauffman's model is a random complex automata where nodes are randomly assembled. Each node σ i receives K inputs from K randomly chosen nodes and the values of σ i at time t + 1 is a random Boolean function of the K inputs at time t . Numerical simulations have shown that the behaviour of this model is very different for K > 2 and K ⩽ 2. It is the purpose of this work to give a simple annealed approximation which predicts K = 2 as the critical value of K . This approximation gives also quantitative predictions for distances between iterated configurations. These predictions agree rather well with the numerical simulations. A possible way of improving this annealed approximation is proposed.
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Neural networks and physical systems with emergent collective computational abilities.
Hopfield, J. J. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.8.2554 · Cited by 19,270
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Metadata
- Authors
- Derrida, B., & Pomeau, Y.
- Venue
- Europhysics Letters (EPL)
- Publisher
- IOP Publishing
- Published
- 1986-01-15
- Volume
- 1
- Issue
- 2
- Pages
- 45-49
- ISSN
- 0295-5075 (ISSN-L)
- 1286-4854
- OpenAlex
- W2065178468
- Cited by
- 706
- References
- 1
- FWCI
- 24.81
- Type
- journal article
- Language
- en
- Open access
- bronze
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