Definition of the Subject
Cellular automata are discrete, agent-based models that can be used for the simulation of complex systems [1]. They are composed of:
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A grid of cells.
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A set of ingredients called agents that can occupy the cells.
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A set of local rules governing the behaviors of the agents.
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Specified initial conditions.
Once these components are defined, a simulation can be carried out. During the simulation the system evolves via a series of discrete time-steps, or iterations, in which the rules are applied to all of the ingredients of the system and the configuration of the system is regularly updated. A striking feature of the cellular automata (CA) models is that they treat not only the ingredients, or agents, of the model as discrete entities, as do the traditional models of physics and chemistry, but in the CA models time (iterations) and space (the cells) are also regarded as discrete, in contrast to the continuous forms assumed for these variables in the traditional,...
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Abbreviations
- Agents:
-
Ingredients under study occupying the cells in the grid.
- Asynchronous:
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Each cell in turn, at random responds to a rule.
- Cells:
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Sections of the grid in which the agents exist.
- Gravity:
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The relative relationship of two agents within the frame of a grid with opposite bound edges.
- Grid:
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The frame containing the cells and the agents.
- Movement:
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The simulation of agent movement between cells accomplished by the disappearance of an agent in a cell and the appearance of that agent in an adjacent cell.
- Neighborhood:
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The cells immediately touching a given cell in the grid.
- Rules:
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Statements of actions to be taken by an agent under certain conditions. They may take the form of a probability of such an action.
- Synchronous:
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All cells in a grid exercise a simultaneous response to a rule.
Bibliography
Primary Literature
Kier LB, Seybold PG, Cheng C-K (2005) Modeling chemical systems using cellular automata. Springer, Dordrecht
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Tofolli T, Margolas N (1987) Cellular automata machines: A new environment for modeling. MIT Press, Cambridge
Wolfram S (2002) A new kind of science. Wolfram Media, Champaign
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Ermentrout GB, Edelstein‐Keshet L (1993) J Theoret Biol 160:97–133
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Wu-Pong S, Cheng C-K (1999) Pharmacokinetic simulations using cellular automata in a pharmacokinetics course. Am J Pharm Educ 63:52–55
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White R (2005) Modelling multi-scale processes in a cellular automata framework. In: Portugali J (ed) Complex artificial environments. Springer, New York, pp 165–178
Kier LB, Cheng C-K (1994) A cellular automata model of water. J Chem Inf Comp Sci 34:647–654
Kier LB, Cheng C-K (1994) A cellular automata model of an aqueous solution. J Chem Inf Comp Sci 34:1334–1341
Kier LB, Cheng C-K, Testa B (1995) A cellular automata model of the hydrophobic effect. Pharm Res 12:615–622
Kier LB, Cheng C-K (1995) A cellular automata model of dissolution. Pharm Res 12:1521–1528
Kier LB, Cheng C-K, Testa B (1997) A cellular automata model of diffusion in aqueous systems. J Pharm Sci 86:774–781
Kier LB, Cheng C-K, Seybold PG (2001) A cellular automata model of aqueous systems. Revs Comput Chem 17:205–238
Cheng C-K, Kier LB (1995) A cellular automata model of oil-water partitioning. J Chem Inf Comput Sci 35:1054–1061
Kier LB, Cheng C-K, Tute M, Seybold PG (1998) A cellular automata model of acid dissociation. J Chem Inf Comp Sci 38:271–278
Seybold PG, Kier LB, Cheng C-K (1997) J Chem Inf Comput Sci 37:386–391
Neuforth A, Seybold PG, Kier LB, Cheng C-K (2000) Cellular automata models of kinetically and thermodynamically controlled reactions, vol A. Int J Chem Kinetic 32:529–534
Seybold PG, Kier LB, Cheng C-K (1998) Stochastic cellular automata models of molecular excited state dynamics. J Phys Chem A 102:886–891
Seybold PG, Kier LB, Cheng C-K (1999) Aurora Borealis: Stochastic cellular automata simulation of the excited state dynamics of Oxygen atoms. Int J Quantum Chem 75:751–756
Okabe H (1978) Photochemistry of small molecules. Wiley, New York, p 370
Moore J, Seybold PG; To be published personal correspondence
Kier LB, Cheng C-K, Testa B (1996) A cellular automata model of enzyme kinetics. J Molec Graph 14:227–234
Kier LB, Bonchev D, Buck G (2005) Modeling biochemical networks: A cellular automata approach. Chem Biodiv 2:233–43
Kier LB, Cheng C-K (2000) A cellular automata model of an anticipatory system. J Molec Graph Model 18:29–35
Kier LB, Cheng C-K, Testa B (1996) Cellular automata model of micelle formation. Pharm Res 13:1419–1426
Kier LB Cheng C-K (1997) A cellular automata model of membrane permeability. J Theor Biol 186:75–85
Kier LB, Cheng C-K, Karnes HT (2000) A cellular automata model of chromatography. Biomed Chrom 14:530–539
Bonchev D (2003) Complexity of protein–protein interaction networks, complexes and pathways. In: Conn M (ed) Handbook of proteomics methods. Humana, New York, pp 451–462
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Selected Bibliography of Works on Cellular Automata
At this time thousands of scientific articles have been published de-
scribing cellular automata studies of topics ranging from applica-
tions dealing with physical and biological systems to investiga-
tions of traffic control and topics in the social sciences. It would be
impossible to describe all of these studies within a limited space,
but it may be useful to provide a short list of representative investi-
gations on a limited variety of topics, permitting starting points for
readers who might wish to further examine applications in these
more narrow subjects. Below we give a short selection of publica-
tions, some of which, although not explicitly referring to CA, cover
the same approach or a related approach.
Artificial Life
Adami C (1998) An introduction to artificial life. Springer, New York
Langton CG, Farmer JD, Rasmussen S, Taylor C (1992) Artificial life, vol II. Addison‐Wesley, Reading
Biological Applications (General)
Maini PK, Deutsch A, Dormann S (2003) Cellular automaton modeling of biological pattern formation. Birkhäuser, Boston
Sigmund K (1993) Games of life: Explorations in ecology, evolution, and behaviour. Oxford University Press, New York
Solé R, Goodman B (2000) Signs of life: How complexity pervades biology. Basic Books, New York; A tour-de-force general introduction to biological complexity, with many examples
Books
Chopard B, Droz M (1998) Cellular automata modeling of physical systems. Cambridge University Press, Cambridge
Gaylord RJ, Nishidate K (1996) Modeling nature: Cellular automata simulations with Mathematica®. Telos, Santa Clara
Griffeath D, Moore C (2003) New constructions in cellular automata. In: Santa Fe Institute Studies in the Sciences of Complexity Proceedings. Oxford University Press, New York
Ilachinski A (2001) Cellular automata: A discrete universe. World Scientific, Singapore
Kier LB, Seybold PG, Cheng C-K (2005) Modeling chemical systems using cellular automata. Springer, Dodrecht
Manneville P, Boccara N, Vishniac GY, Bidaux R (1990) Cellular automata and modeling of complex physical systems. Springer, New York, pp 57–70
Schroeder M (1991) Fractals, chaos, power laws. WH Freeman, New York
Toffoli T, Margolus N (1987) Cellular automata machines: A new environment for modeling. MIT Press, Cambridge
Wolfram S (1994) Cellular automata and complexity: Collected papers. Westview Press, Boulder
Wolfram S (2002) A new kind of science. Wolfram Media, Champaign
Emergent Properties
Gruner D, Kapral R, Lawniczak AT (1993) Nucleation, domain growth, and fluctuations in a bistable chemical system. J Chem Phys 96:2762–2776
Hopfield JJ (1982) Neural networks and physical systems with emergent collective computational abilities. Proc Nat Acad Sci USA 79:2554–2558
Kauffman S (1984) Emergent properties in random complex automata. Physica D 10:145–156
Ottino JM (2004) Engineering complex systems. Nature 427:399
Evolution
Farmer JD, Kauffman SA, Packard NH (1986) Autocatalytic replication of polymers. Physica D 22:50–67
Solé RV, Bascompté J, Manrubia SC (1996) Extinctions: Bad genes or weak chaos? Proc Roy Soc Lond B 263:1407–1413
Solé RV, Manrubia SC (1997) Criticality and unpredictability in macroevolution. Phys Rev E 55:4500–4508
Solé RV, Manrubia SC, Benton M, Bak P (1997) Self‐similarity of extinction statistics in the fossil record. Nature 388:764–767
Solé RV, Montoya JM, Erwin DH (2002) Recovery from mass extinction: Evolutionary assembly in large-scale biosphere dynamics. Phil Trans Royal Soc 357:697–707
Excited State Phenomena
Seybold PG, Kier LB, Cheng C-K (1998) Stochastic cellular automata models of molecular excited‐state dynamics. J Phys Chem A 102:886–891; Describes general cellular automata models of molecular excited states
Seybold PG, Kier LB, Cheng C-K (1999) Aurora Borealis: Stochastic cellular automata simulations of the excited‐state dynamics of Oxygen atoms. Int J Quantum Chem 75:751–756; This paper examines the emissions and excited‐state transitions of atomic Oxygen responsible for some of the displays of the Aurora Borealis
First-Order Chemical Kinetics
Hollingsworth CA, Seybold PG, Kier LB, Cheng C-K (2004) First-order stochastic cellular automata simulations of the Lindemann mechanism. Int J Chem Kinetic 36:230–237
Neuforth A, Seybold PG, Kier LB, Cheng C-K (2000) Cellular automata models of kinetically and thermodynamically controlled reactions. Int J Chem Kinetic 32:529–534; A study of kinetic and thermodynamic reaction control
Seybold PG, Kier LB, Cheng C-K (1997) Simulation of first-order chemical kinetics using cellular automata. J Chem Inf Comput Sci 37:386–391; This paper illustrates a number of first-order cellular automata models
Fluid Flow
Malevanets A, Kapral R (1998) Continuous‐velocity lattice‐gas model for fluid flow. Europhys Lett 44:552
Game of Life
Alpert M (1999) Not just fun and games. Sci Am 40:42; A profile of John Horton Conway
Gardner M (1970) The fantastic combinations of John Conway’s new solitaire game “life”. Sci Amer 223:120–123
Gardner M (1971) On cellular automata, self-reproduction, the Garden of Eden and the game of “life”. Sci Amer 224:112–117"
Note: There are many examples on the web of applets that allow
you to play the Game of Life. Since these come and go, you are
urged to locate them using a search engine.
Geology
Barton CC, La Pointe PR (1995) Fractals in petroleum geology and earth processes. Plenum, New York
Turcotte DL (1997) Fractals and chaos in geology and geophysics, 2nd edn. Cambridge University Press, New York
Historical Notes
Ulam SM (1952) Random processes and transformations. Proc Int Congr Math 2:264, held in 1950
Ulam SM (1976) Adventures of a mathematician. Charles Scribner’s Sons, New York
Von Neumann J (1966) Burks A (ed) Theory of self‐replicating automata. University of Illinois Press, Urbana
Zuse K (1982) The computing universe. Int J Theoret Phys 21:589
Liquid Phase Interactions
Cheng C-K, Kier LB (1995) A cellular automata model of oil-water partitioning. J Chem Info Comput Sci 35:1054–1059
Kier LB, Cheng C-K, Testa B (1996) A cellular automata model of micelle formation. Pharm Res 13:1419–1422
Malevanets A, Kapral R (1999) Mesoscopic model for solvent dynamics. J Chem Phys 110:8605–8613
Oscillations
Chavez F, Kapral R (2002) Oscillatory and chaotic dynamics in compartmentalized geometries. Phys Rev E 65:056203
Chavez F, Kapral R, Rousseau G, Glass L (2001) Scroll waves in spherical shell geometries. Chaos 11:757
Goryachev A, Strizhak P, Kapral R (1997) Slow manifold structure and the emergence of mixed-mode oscillations. J Chem Phys 107:2881
Hemming C, Kapral R (2002) Phase front dynamics in inhomogeneously forced oscillatory systems. Physica A 306:199
Pattern Formation
Kapral R, Showalter K (1994) Chemical waves and patterns. Kluwer, Dordrecht
Parrish JK, Edelstein‐Keshet L (1999) Complexity, pattern, and evolutionary trade-offs in animal aggregation. Science 284:99–101
Veroney JP, Lawniczak AT, Kapral R (1996) Pattern formation in heterogeneous media. Physica D 99:303–317
Physics Applications
Signorini J (1990) Complex computing with cellular automata. In: Manneville P, Boccara N, Vishniac GY, Bidaux R (eds) Cellular automata and modeling of complex physical systems. Springer, New York, pp 57–70
Toffoli T (1984) Cellular automata as an alternative (rather than an approximation of) differential equations in modeling physics. Physica D 10:117–127
Vichniac GY (1984) Simulating physics with cellular automata. Physica D 10:96–116
Population Biology and Ecology
Bascompté J, Solé RV (1994) Spatially‐induced bifurcations in single species population dynamics. J Anim Ecol 63:256–264
Bascompté J, Solé RV (1995) Rethinking complexity: Modelling spatiotemporal dynamics in ecology. Trends Ecol Evol 10:361–366
Bascompté J, Solé RV (1996) Habitat fragmentation, extinction thresholds in spatialy explicit models. J Anim Ecol 65:465
Deutsch A, Lawniczak AT (1999) Probabilistic lattice models of collective motion, aggregation: From individual to collective dynamics. J Math Biosci 156:255–269
Fuks H, Lawniczak AT (2001) Individual‐based lattice models for the spatial spread of epidemics. Discret Dyn Nat Soc 6(3):1–18
Gamarra JGP, Solé RV (2000) Bifurcations, chaos in ecology: Lynx returns revisited. Ecol Lett 3:114–121
Levin SA, Grenfell B, Hastings A, Perelson AS (1997) Mathematical, computational challenges in population biology, ecosystems science. Science 275:334–343
Montoya JM, Solé RV (2002) Small world patterns in food webs. J Theor Biol 214:405–412
Nowak MA, Sigmund K (2004) Population dynamics in evolutionary ecology. In: Keinan E, Schechter I, Sela M (eds) Life sciences for the 21st century. Wiley-VCH, Cambridge, pp 327–334
Solé RV, Alonso D, McKane A (2000) Connectivity, scaling in S‑species model ecosystems. Physica A 286:337–344
Solé RV, Manrubia SC, Kauffman S, Benton M, Bak P (1999) Criticality, scaling in evolutionary ecology. Trends Ecol Evol 14:156–160
Solé RV, Montoya JM (2001) Complexity, fragility in ecological networks. Proc Roy Soc 268:2039–2045
Random Walks
Berg HC (1983) Random walks in biology. Princeton University Press, Princeton
Hayes B (1988) How to avoid yourself. Am Sci 86:314–319
Lavenda BH (1985) Brownian motion. Sci Am 252(2):70–85
Shlesinger MF, Klafter J (1989) Random walks in liquids. J Phys Chem 93:7023–7026
Slade G (1996) Random walks. Am Sci 84:146–153
Weiss GH (1983) Random walks, their applications. Am Sci 71:65–71
Reviews
Kapral R, Fraser SJ (2001) Chaos, complexity in chemical systems. In: Moore JH, Spencer ND (eds) Encyclopedia of chemical physics, physical chemistry, vol III. Institute of Physics Publishing, Philadelphia, p 2737
Kier LB, Cheng C-K, Testa (1999) Cellular automata models of biochemical phenomena. Future Generation Compute Sci 16:273–289
Kier LB, Cheng C-K, Seybold PG (2000) Cellular automata models of chemical systems. SAR QSAR Environ Res 11:79–102
Kier LB, Cheng C-K, Seybold PG (2001) Cellular automata models of aqueous solution systems. In: Lipkowitz KM, Boyd DB (eds) Reviews in computational chemistry, vol 17. Wiley-VCH, New York, pp 205–225
Turcotte DL (1999) Self‐organized criticality. Rep Prog Phys 62:1377–1429
Wolfram S (1983) Cellular automata. Los Alamos Sci 9:2–21
Second‐Order Chemical Kinetics
Boon JP, Dab D, Kapral R, Lawniczak AT (1996) Lattice‐gas automata for reactive systems. Phys Rep 273:55–148
Chen S, Dawson SP, Doolen G, Jenecky D, Lawiczak AT (1995) Lattice methods for chemically reacting systems. Comput Chem Engr 19:617–646
Self‐Organized Criticality
Bak P (1996) How nature works. Springer, New York
Bak P, Tang C, Wiesenfeld K (1987) Self‐organized criticality: An explanation for 1/f noise. Phys Rev Lett 59:381–384; A classic paper introducing the “sandpile” cellular automaton
Turcotte DL (1999) Self‐organized criticality. Rep Prog Phys 62:1377–1429
Social Insect Behavior
Cole BJ (1991) Short-term activity cycles in ants: Generation of periodicity by worker inaction. Amer Nat 137:144–259
Cole BJ (1996) Mobile cellular automata models of ant behavior: Movement activity of Leptothorax Allardycei. Amer Nat 148:1–15
Deneubourg J-L, Goss S, Franks NR, Pasteels JM (1989) The blind leading the blind: Modeling chemically mediated Army ant raid patterns. J Insect Behav 2:719–772
Goss S, Deneubourg J-L (1988) Autocatalysis as a source of synchronized rhythmical activity in social insects. Insectes Sociaux 35:310–315
Solé RV, Miramontes O, Goodwin BC (1993) Oscillations, chaos in ant societies. J Theoret Biol (1993) 161:343–357
Social Sciences
Gaylord RJ (1998) D’Andria LJ (1998) Simulating society: A Mathematica toolkit for modeling socioeconomic behavior. Springer/Telos, New York
Mandelbrot BB (1982) The fractal geometry of nature. Freeman, San Francisco
Traffic Rules
Huang P-H, Kong L-J, Liu M-R (2002) A study of a main-road cellular automata traffic flow model. Chin Phys 11:678–683
Nagel K, Wolf DE, Wagner P, Simon P (1998) Two-lane rules for cellular automata: A systematic approach. Phys Rev E 58:1425–1437
Water
Kier LB, Cheng C-K (1994) A cellular automata model of water. J Chem Info Comput Sci 34:647
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Kier, L.B., Seybold, P.G. (2009). Cellular Automata Modeling of Complex Biochemical Systems. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_56
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