Abstract
This paper reviews a class of generic dissipative dynamical systems called N-K models. In these models, the dynamics of N elements, defined as Boolean variables, develop step by step, clocked by a discrete time variable. Each of the N Boolean elements at a given time is given a value which depends upon K elements in the previous time step. We review the work of many authors on the behavior of the models, looking particularly at the structure and lengths of their cycles, the sizes of their basins of attraction, and the flow of information through the systems. In the limit of infinite N, there is a phase transition between a chaotic and an ordered phase, with a critical phase in between. We argue that the behavior of this system depends significantly on the topology of the network connections. If the elements are placed upon a lattice with dimension d,the system shows correlations related to the standard percolation or directed percolation phase transition on such a lattice. On the other hand, a very different behavior is seen in the Kauffman net in which all spins are equally likely to be coupled to a given spin. In this situation, coupling loops are mostly suppressed, and the behavior of the system is much more like that of a mean field theory. We also describe possible applications of the models to, for example, genetic networks, cell differentiation, evolution, democracy in social systems and neural networks.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abarbanel, H. D. I., M. I. Rabinovich, A. Selverston, and M. V. Bazhenov [ 1996 ], Synchronization in Neural Networks, Physics-Uspeki 39, 337–362.
Albert, R. and A.-L. Barabâsi [ 2000 ], Dynamics of Complex Systems: Scaling Laws for the Period of Boolean Networks, Physical Review Letters 84, 56605663.
Albert, R. and A.-L. Barabâsi [ 2002 ], Statistical Mechanics of Complex Networks, Reviews of Modern Physics 74, 47–97.
Alberts, B., D. Bray, J. Lewis, M. Raff, K. Roberts, and J. D. Watson [ 1994 ], Molecular Biology of the Cell, Third Edition. Garland Publishing, New York.
Andrecut, M. and M. K. Ali [ 2001 ], Chaos in a Simple Boolean Network, International Journal of Modern Physics B 15, 17–23.
Atlan, H., F. Fogelman-Soulie, J. Salomon, and G. Weisbuch [ 1981 ], Random Boolean Networks, Cybernetics and Systems 12, 103–121.
Bagley, R. J. and L. Glass [ 1996 ], Counting and Classifying Attractors in High Dimensional Dynamical Systems, Journal of Theoretical Biology 183, 269–284.
Baillie, C. F. and D. A. Johnston [ 1994 ], Damaging 2D Quantum Gravity, Physics Letters B 326, 51–56.
Bak, P., H. Flyvbjerg, and B. Lautrup [ 1992 ], Coevolution in a Rugged Fitness Landscape, Physical Review A 46, 6724–6730.
Barabâsi, A.-L. [ 2002 ], Linked: The New Science of Networks. Perseus Publising, Cambridge, Massachusetts.
Bastolla, U. and G. Parisi [ 1996 ], Closing Probabilities in the Kauffman Model: an Annealed Computation, Physica D 98, 1–25.
Bastolla, U. and G. Parisi [ 1997 ], A Numerical Study of the Critical Line of Kauffman Networks, Journal of Theoretical Biology 187, 117–133.
Bastolla, U. and G. Parisi [ 1998a ], The Modular Structure of Kauffman Networks, Physica D 115, 219–233.
Bastolla, U. and G. Parisi]1998b], Relevant Elements, Magnetization and Dynamical Properties in Kauffman Networks: a Numerical Study, Physica D 115203–218.
Bhattacharjya, A. and S. Liang [ 1996a ], Median Attractor and Transients in Random Boolean Nets, Physica D 95, 29–34.
Bhattacharjya, A. and S. Liang[1996b], Power-Law Distributions in Some Random Boolean Networks, Physical Review Letters 77, 1644–1647.
Bilke, S. and F. Sjunnesson [ 2001 ], Stability of the Kauffman Model, Physical Review E 65, 016129.
Bornholdt, S. [ 1998 ], Genetic Algorithm Dynamics on a Rugged Landscape, Physical Review E 57, 3853–3860.
Bornholdt, S. and T. Rohlf [ 2000 ], Topological Evolution of Dynamical Networks: Global Criticality From Local Dynamics, Physical Review Letters 84, 61146117.
Bornholdt, S. and K. Sneppen [ 1998 ], Neutral Mutations and Punctuated Equi- librium in Evolving Genetic Networks, Physical Review Letters 81, 236–239.
Bornholdt, S. and K. Sneppen [ 2000 ], Robustness as an Evolutionary Principle, Proc. Royal Soc. Lond. B 266, 2281–2286.
Bull, L. [ 1999 ], On the Baldwin Effect, Artificial Life 5, 241–246.
Burda, Z., J. Jurkiewicz, and H. Flyvbjerg [ 1990 ], Classification of Networks of Automata By Dynamic Mean-Field Theory, Journal of Physics A: Mathematical and General 23, 3073–3081.
Castagnoli, G. [ 1998 ], Merging Quantum Annealing Computation and Particle Statistics: A Prospect in the Search of Efficient Solutions to Intractable Problems, International Journal of Theoretical Physics 37, 457–462.
Cheng, B. and D. M. Titterington [ 1994 ], Neural networks: a review from a statistical perspective, Statistical Science 9, 2–54.
Coppersmith, S. N., L. P. Kadanoff, and Z. Zhang [ 2001a ], Reversible Boolean Networks I: Distribution of Cycle Lengths, Physica D 149, 11–29.
Coppersmith, S. N., L. P. Kadanoff, and Z. Zhang [ 2001b ], Reversible Boolean Networks II: Phase Transitions, Oscilations and Local Structures., Physica D 157, 54–74.
Corsten, M. and P. Poole [ 1988 ], Initiation of Damage in the Kauffman Model, Journal of Statistical Physics 50, 461–463.
Dawkins, R. [ 1986 ], The Blind Watchmaker. W.W. Norton and Company, USA.
Dawkins, R. [ 1989 ], The Selfish Gene. Oxford University Press, Oxford, second edition.
De Sales, J. A., M. L. Martins, and D. A. Stariolo [ 1997 ], Cellular Automata Model for Gene Networks, Physical Review E 55, 3262–3270.
Derrida, B. [ 1980 ], Random-Energy Model: Limit of a Family of Disordered Models, Physical Review Letters 45, 79–82.
Derrida, B. [ 1987a ], Dynamical Phase Transitions in Non-Symmetric Spin Glasses, Journal of Physics A: Mathematical and General 20, L721 — L725.
Derrida, B. [ 1987b ], Valleys and Overlaps in Kauffman Model, Philosophical Magazine B: Physics of Condensed Matter, Statistical Mechanics, Electronic, Optical and Magnetic Properties 56, 917–923.
Derrida, B. and D. Bessis [ 1988 ], Statistical Properties of Valleys in the Annealed Random Map Model, Journal of Physics A: Mathematical and General 21, L509 — L515.
Derrida, B. and H. Flyvbjerg [ 1986 ], Multivalley Structure in Kauffman Model–Analogy With Spin-Glasses, Journal of Physics A: Mathematical and General 19, 1003–1008.
Derrida, B. and H. Flyvbjerg [ 1987a ], Distribution of Local Magnetizations in Random Networks of Automata, Journal of Physics A: Mathematical and General 20, L1107 — L1112.
Derrida, B. and H. Flyvbjerg [ 1987b ], The Random Map Model: a Disordered Model With Deterministic Dynamics, Journal De Physique 48, 971–978.
Derrida, B., E. Gardner, and A. Zippelius [ 1987 ], An Exactly Solvable Asymmetric Neural Network Model, Europhysics Letters 4, 167–173.
Derrida, B. and Y. Pomeau [ 1986 ], Random Networks of Automata–a Simple Annealed Approximation, Europhysics Letters 1, 45–49.
Derrida, B. and D. Stauffer [ 1986 ], Phase-Transitions in Two-Dimensional Kauffman Cellular Automata, Europhysics Letters 2, 739–745.
Derrida, B. and G. Weisbuch [ 1986 ], Evolution of Overlaps Between Configura- tions in Random Boolean Networks, Journal De Physique 47, 1297–1303.
Domany, E. and W. Kinzel [ 1984 ], Equivalence of Cellular Automata to Ising Models and Directed Percolation, Physical Review Letters 53, 311–314.
Fambrough, D., K. Mcclure, A. Kazlauskas, and E. S. Lander [ 1999 ], Diverse Signaling Pathways Activated By Growth Factor Receptors Induce Broadly Overlapping, Rather That Independent, Sets of Genes, Cell 97, 727–741.
Farmer, J. D. [ 1990 ], A Roseta Stone for Connectionism, Physica D 42, 153–187.
Flyvbjerg, H. [ 1988 ], An Order Parameter for Networks of Automata, Journal of Physics A: Mathematical and General 21, L955 — L960.
Flyvbjerg, H. [ 1989 ], Recent Results for Random Networks of Automata, Acta Physica Polonica B 20, 321–349.
Flyvbjerg, H. and N. J. Kjaer [ 1988 ], Exact Solution of Kauffman Model with Connectivity One, Journal of Physics A: Mathematical and General 21, 16951718.
Flyvbjerg, H. and B. Lautrup [ 1992 ], Evolution in a Rugged Fitness Landscape, Physical Review A 46, 6714–6723.
Fogelman-Soulie, F. [ 1984 ], Frustration and Stability in Random Boolean Networks, Discrete Applied Mathematic 9, 139–156.
Fogelman-Soulie, F. [ 1985 ], Parallel And Sequential Computation On Boolean Networks, Theor. Comp. Sci. 40, 275–300.
Genoud, T. and J.-P. Metraux [ 1999 ], Crosstalk in Plant Cell Signaling: Structure and Function of the Genetic Network, Trends in Plant Science 4, 503–507.
Glass, L. and C. Hill [ 1998 ], Ordered and Disordered Dynamics in Random Networks, Europhysics Letters 41, 599–604.
Golinelli, O. and B. Derrida [ 1989 ], Barrier Heights in the Kauffman Model, Journal De Physique 50, 1587–1601.
Griffiths, R. [ 1969 ], Nonanalytic Behavior Above the Critical Point in a Random Ising Ferromagnet, Physical Review Letters 23, 17–19.
Hansen, A. [ 1988a ], A Connection Between the Percolation Transition and the Onset of Chaos In the Kauffman Model, Journal of Physics A: Mathematical and General 21, 2481–2486.
Hansen, A. [ 1988b ], Percolation and Spreading of Damage in a Simplified Kauffman Model, Physica A 153, 47–56.
Harris, B. [ 1960 ], Probability Distributions Related to Random Mappings, Annals of Mathematical Statistics 31, 1045–1062.
Herrmann, H. J. [ 1992 ], Simulation of Random Growth-Processes, Topics in Applied Physics 71, 93–120.
Hilhorst, H. J. and M. Nijmeijer [ 1987 ], On the Approach of the Stationary State in Kauffmans Random Boolean Network, Journal De Physique 48, 185–191.
Hopfield, J. J. [ 1982 ], Neural Networks and Physical Systems with Emergent Collective Computational Abilities, Proceedings of the National Academy of Sciences 79, 2554–2558.
Hopfield, J. J. [ 1999 ], Brain, Neural Networks and Computation, Reviews of Modern Physics 71, 5431–5437.
Huang, S. and D. E. Ingber [ 2000 ], Shape-Dependent Control of Cell Growth, Differentiation, and Apoptosis: Switching Between Attractors in Cell Regulatory Networks, Experimental Cell Research 261, 91–103.
Huepe, C. and M. Aldana-González [ 2002 ], Dynamical Phase Transition in a Neural Network Model with Noise: An Exact Solution, Journal of Statistical Physics 108, (3/4), 527–540.
Ito, K. and Y.-P. Gunji [ 1994 ], Self-Organization of Living Systems Towards Criticality at the Edge of Chaos, Biosystems 33, 17–24.
Jan, N. [1988], Multifractality and the Kauffman Model Journal of Physics A: Mathematical and General 21 L899–L902.
Kadanoff, L. P. [2000] Statistical Physics: Statics Dynamics and Renormalization. World Scientific, Singapore.
Kauffman, S. [1984], Emergent Properties in Random Complex Automata Physica D 10 145–156.
Kauffman, S. A. [ 1969 ], Metabolic Stability and Epigenesis in Randomly Constructed Nets, Journal of Theoretical Biology 22, 437–467.
Kauffman, S. A. [ 1974 ], The Large Scale Structure and Dynamics of Genetic Control Circuits: an Ensemble Approach, Journal of Theoretical Biology 44, 167–190.
Kauffman, S. A. [ 1990 ], Requirements for Evolvability in Complex Systems–Orderly Dynamics and Frozen Components, Physica D 42, 135–152.
Kauffman, S. A. [1993] The Origins of Order: Self-Organization and Selection in Evolution. Oxford University Press, Oxford.
Kauffman, S. A. [1995] At Home in the Universe: the Search for Laws of Self-Organization and Complexity. Oxford University Press, Oxford.
Kauffman, S. A. and W. G. Macready [ 1995 ], Search Strategies for Applied Molecular Evolution, Journal of Theoretical Biology 173, 427–440.
Kauffman, S. A. and E. D. Weinberger [ 1989 ], The NK Model of Rugged Fitness Landscapes and Its Application To Maturation of the Immune Response, Journal of Theoretical Biology 141, 211–245.
Kaufman, J. H., D. Brodbeck, and O. M. Melroy [ 1998 ], Critical Biodiversity, Conservation Biology 12, 521–532.
Kirillova, O. V. [ 1999 ], Influence of a Structure on Systems Dynamics on Example of Boolean Networks, International Journal of Modern Physics C 10, 12471260.
Klüver, J. and J. Schmidt [ 1999 ], Control Parameters in Boolean Networks and Cellular Automata Revisited from a Logical and Sociological Point of View, Complexity 5, 45–52.
Krapivsky, P. L., S. Redner, and F. Leyvraz [ 2000 ], Connectivity of Growing Random Networks, Physical Review Letters 85, 4629–4632.
Kulakowski, K. [ 1995 ], Relaxation and Limit-Cycles in a Global Version of the Quenched Kauffman Model, Physica A 216, 120–127.
Kürten, K. E. [1988a], Correspondence Between Neural Threshold Networks and Kauffman Boolean Cellular Automata Journal of Physics A: Mathematical and General 21 L615–L619.
Kürten, K. E. [ 1988b ], Critical Phenomena in Model Neural Netwoks, Physics Letters A 129, 157–160.
Kürten, K. E. and H. Beer [ 1997 ], Inhomogeneous Kauffman Models at the Borderline Between Order and Chaos, Journal of Statistical Physics 87, 929–935.
Lam, P. M. [ 1988 ], A Percolation Approach to the Kauffman Model, Journal of Statistical Physics 50, 1263–1269.
Langton, C. G. [ 1990 ], Computations at the Edge of Chaos: Phase Transitions and Emergent Computation, Physica D 42, 12–37.
Lee, C.-Y. and S. K. Han [ 1998 ], Evolutionary Optimization Algorithm By En-tropic Sampling, Physical Review E 57, 3611–3617.
Levitan, B. and S. Kauffman [ 1995 ], Adaptive Walks With Noisy Fitness Measurements, Molecular Diversity 1, 53–68.
Little, W. A. [ 1974 ], The Existence of Persistent States in the Brain, Mathematical Bioscience 19, 101–120.
Luczak, T. and J. E. Cohen [ 1991 ], Stability of Vertices in Random Boolean Cellular Automata, Random Structures and Algorithms 2, 327–334. reference from Lynch.
Luque, B. and R. V. Solé [ 1997a ], Controlling Chaos in Random Boolean Networks, Europhysics Letters 37, 597–602.
Luque, B. and R. V. Solé [ 1997b ], Phase Transitions in Random Networks: Simple Analytic Determination of Critical Points, Physical Review E 55, 257–260.
Luque, B. and R. V. Solé [1998], Stable Core and Chaos Control in Random Boolean Networks, Journal of Physics A: Mathematical and General 31, 1533 1537.
Luque, B. and R. V. Solé [ 2000 ], Lyapunov Exponents in Random Boolean Networks, Physica A 284, 33–45.
Lynch, J. F. [ 1993a ], Antichaos in a Class of Random Boolean Cellular-Automata, Physica D 69, 201–208.
Lynch, J. F. [ 1993b ], A Criterion for Stability in Random Boolean Cellular-Automata, Los Alamos Data Base http://arXiv.org/abs/adaporg/9305001.
Lynch, J. F. [ 1995 ], On the Threshold of Chaos in Random Boolean Cellular-Automata, Random Structures and Algorithms 6, 239–260.
Ma, S. [ 1976 ], Modern Theory of Critical Phenomena. Benjamin, Reading Pa.
Macisaac, A. B., D. L. Hunter, M. J. Corsten, and N. Jan [ 1991 ], Determinism and Thermodynamics–Ising Cellular Automata, Physical Review A 43, 3190–319.
Manrubia, S. C. and A. S. Mikhailov [ 1999 ], Mutual Synchronization and Clustering in Randomly Coupled Chaotic Dynamical Networks, Physical Review E 60, 1579–1589.
McCulloch, W. S. and W. Pitts [ 1943 ], A Logical Calculus of Ideas Immanent in Nervous Activity, Bulletin of Mathematical Biophysics 5, 115–133.
Mestl, T., R. J. Bagley, and L. Glass [ 1997 ], Common Chaos in Arbitrarily Complex Feedback Networks, Physicl Review Letters 79, 653–656.
Metropolis, N. and S. Ulam [ 1953 ], A Property of Randomness of an Arithmetical Function, American Mathematical Monthly 60, 252–253.
Mezard, M., G. Parisi, and M. A. Virasoro [ 1987 ], Spin Glass Theory and Beyond. World Scientific, Singapore.
Miranda, E. N. and N. Parga [ 1988 ], Ultrametricity in the Kauffman Model - a Numerical Test, Journal of Physics A: Mathematical and General 21, L357 — L361.
Miranda, E. N. and N. Parga [ 1989 ], Noise Effects in the Kauffman Model, Europhysics Letter 10, 293–298.
Nirei, M. [ 1999 ], Critical Fluctuations in a Random Network Model, Physica A 269, 16–23.
Obukhov, S. P. and D. Stauffer [1989], Upper Critical Dimension of Kauffman Cellular Automata, Journal of Physics A: Mathematical and General 22, 1715 1718.
Ohta, T. [ 1997a ], The Meaning of Near-Neutrality at Coding and Non-Coding Regions, Gene 205, 261–267.
Ohta, T. [ 1997b ], Role of Random Genetic Drift in the Evolution of Interactive Systems, Journal of Molecular Evolution 44, S9 — S14.
Ohta, T. [ 1998 ], Evolution By Nearly Neutral Mutations, Genetica 103, 83–90.
Owezarek, A., A. Rechnitzer, and A. J. Guttmann [ 1997 ], On the Hulls of Directed Percolation Clusters, Journal of Physics A: Mathematical and General 30, 6679–6691.
Petters, D. [ 1997 ], Patch Algorithms in Spin Glasses, International Journal of Modern Physics C 8, 595–600.
Preisler, H. D. and S. Kauffman [ 1999 ], A Proposal Regarding the Mechanism Which Underlies Lineage Choice During Hematopoietic Differentiation, Leukemia Research 23, 685–694.
Qu, X., L. Kadanoff, and M. Aldana [ 2002 ], Numerical and Theoretical Studies of Noise Effects in Kauffman Model, Journal of Statistical Physics, 109, (5/6), 967–986.
Randeria, M., J. Sethna, and R. Palmer [ 1985 ], Low-Frequency Relaxation in Ising Spin-Glasses, Physical Review Letters 54, 1321–1324.
Rosser, J. B. and L. Schoenfeld [ 1962 ], Approximate Formulas for some Functions of Prime Numbers, Illinois Journal of Mathematics 6, 64–94.
Sakai, K. and Y. Miyashita [ 1991 ], Neural Organization for the Long-TermMemory of Paired Associates, Nature 354, 152–155.
Serra, R. and M. Villani [ 1997 ], Modelling Bacterial Degradation of Organic Compounds With Genetic Networks, Journal of Theoretical Biology 189, 107119.
Shelling, T. C. [ 1971 ], Dynamic Models of Segregation, Journal of Mathematical Sociology 1, 143–186.
Sherrington, D. and K. Y. M. Wong [ 1989 ], Random Boolean Networks for Autoassociative Memory, Physics Reports: Review Section of Physics Letters 184, 293–299.
Sherrington, D. and S. Kirkpatrick [ 1975 ], Solvable Model of a Spin-Glass, Physical Review Letters 35, 1792–1796.
Sibani, P. and A. Pedersen [ 1999 ], Evolution Dynamics in Terraced NK Landscapes, Europhysics Letters 48, 346–352.
Simon, H. A. [ 1969 ], The Sciences of the Artificial. The MIT Press, Cambridge, MA.
Solov, D., A. Burnetas, and M.-C. Tsai [ 1999 ], Understanding and Attenuating the Complexity Catastrophe In Kauffman’s NK Model of Genome Evolution, Complexity 5, 53–66.
Solow, D., A. Burnetas, T. Roeder, and N. S. Greenspan [ 1999 ], Evolutionary Consequences of Selected Locus-Specific Variations In Epistasis and Fitness Contribution in Kauffman’s NK Model, Journal of Theoretical Biology 196, 181–196.
Somogyi, R. and C. A. Sniegoski [ 1996 ], Modeling the Complexity of Genetic Networks: Understanding Multigenetic and Pleiotropic Regulation, Complexity 1, 45–63.
Somogyvdri, Z. and S. Payrits [ 2000 ], Length of State Cycles of Random Boolean Networks: an Analytic Study, Journal of Physics A: Mathematical and General 33, 6699–6706.
Stadler, P. F. and R. Happel [ 1999 ], Random Field Models for Fitness Landscapes, Journal of Mathematical Biology 38, 435–478.
Stauffer, D. [ 1985 ], Introduction to Percolation Theory. Taylor and Francis, London.
Stauffer, D. [ 1994 ], Evolution By Damage Spreading in Kauffman Model, Journal of Statistical Physics 74, 1293–1299.
Stauffer, D. [ 1987a ], On Forcing Functions in Kauffman Random Boolean Networks, Journal of Statistical Physics 46, 789–794.
Stauffer, D. [ 1987b ], Random Boolean Networks–Analogy With Percolation, Philosophical Magazine B: Physics of Condensed Matter, Statistical Mechanics, Electronic, Optical and Magnetic Properties 56, 901–916.
Stauffer, D. [ 1988 ], Percolation Thresholds in Square-Lattice Kauffman Model, Journal of Theoretical Biolog 135, 255–261.
Stauffer, D. [ 1989 ], Hunting for the Fractal Dimension of the Kauffman Model, Physica D 38, 341–344.
Stauffer, D. [ 1991 ], Computer Simulations of Cellular Automata, Journal of Physics A: Mathematical and General 24, 909–927.
Stern, M. D. [ 1999 ], Emergence of Homeostasis and Noise Imprinting in an Evolution Model, Proceedings of the National Academy of Sciences of the U.S.A. 96, 10746–10751.
Stölzle, S. [ 1988 ], Universality Two-Dimensional Kauffman Model for Parallel and Sequential Updating, Journal of Statistical Physics 53, 995–1004.
Strogatz, S. H. [ 2001 ], Exploring Complex Networks, Nature 410, 268–276.
Thieffry, D. and D. Romero [ 1999 ], The Modularity of Biological Regulatory Networks, Biosystems 50, 49–59.
Toffoli, T. and N. H. Margolus [ 1990 ], Invertible Cellular Automata: a Review, Physica D 45, 229–253.
Volkert, L. G. and M. Conrad [ 1998 ], The Role of Weak Interactions in Biological Systems: the Dual Dynamics Model, Journal of Theoretical Biology 193, 287306.
Waelbroeck, H. and F. Zertuche [ 1999 ], Discrete Chaos, Journal of Physics A: Mathematical and General 32, 175–189.
Wang, L., E. E. Pichler, and J. Ross [ 1990 ], Oscillations and Chaos in Neural Networks an Exactly Solvable Model, Proceedings of the National Academy of Sciences of the United States of America 87, 9467–9471.
Weinberger, E. D. [ 1991 ], Local Properties of Kauffman NK Model–a Tunably Rugged Energy Landscape, Physical Review A 44, 6399–6413.
Weisbuch, G. and D. Stauffer [ 1987 ], Phase Transitions in Cellular Random Boolean Networks, Jounal De Physique 48, 11-18.
Wilke, C. O., C. Ronnenwinkel, and T. Martinetz [ 2001 ], Dynamic Fitness Landscapes in Molecular Evolution, Physics Reports 349, 395–446.
Wolfram, S. [ 1983 ], Statistical Mechanics of Cellular Automata, Reviews of Modern Physics 55, 601–644.
Wuensche, A. [ 1999 ], Discrete Dynamical Networks and their Attractor Basins, Complexity International 6, http://www.csu.edu.au/ci/idx—volume.html.
Zawidzki, T. W. [ 1998 ], Competing Models of Stability in Complex, Evolving Systems: Kauffman Vs. Simon, Biology and Philosophy 13, 541–554.
Zoli, M., D. Guidolin, K. Fuxe, and L. F. Agnati [ 1996 ], The Receptor Mosaic Hypothesis of the Engram: Possible Relevance of Boolean Network Modeling, International Journal of Neural Systems 7, 363–368.
Editor information
Editors and Affiliations
Additional information
To Larry Sirovich, on the occasion of his 70th birthday.
Rights and permissions
Copyright information
© 2003 Springer-Verlag New York, Inc.
About this chapter
Cite this chapter
Aldana, M., Coppersmith, S., Kadanoff, L.P. (2003). Boolean Dynamics with Random Couplings. In: Kaplan, E., Marsden, J.E., Sreenivasan, K.R. (eds) Perspectives and Problems in Nolinear Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-21789-5_2
Download citation
DOI: https://doi.org/10.1007/978-0-387-21789-5_2
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4684-9566-9
Online ISBN: 978-0-387-21789-5
eBook Packages: Springer Book Archive