
Artificial life 

Introduction
to Cellular Automata  
The number of possible cellular automata is potentially infinite. In this context, Wolfram wondered about the existence of cellular automata's general behaviour rules^{22}. S. Wolfram studied one dimensional
automata, with two states and a neighbourhood of 2. He only
considered as "legal" the automata that firstly eliminate any cell
without neighbour, and secondly, are symmetric. There are then
only 32 "legal" automata that Wolfram systematically studied. This study showed that, according to the author, numerous cellular automata, and maybe all of them, fall into four basic classes. Class I evolution leads to an homogeneous state. Class I automata (rule 36) Class II Evolution leads to simple or periodic structures. Class II automata (rule 40) Class III Evolution leads to chaotic states. Class III automata (rule 18) Class IV Evolution leads to complex global structures. Class IV automata (rule 20) According to Wolfram, cellular automata
belonging to class IV generate structures that are strongly
reminiscent of the game of life. Yet it is known that this
cellular automaton has the computational universality property.
This means that : "Cellular Automata may be viewed as
computers, in which data represented by initial configurations
is processed by time evolution. Computational universality
implies that suitable initial configurations can specify
arbitrary algorithmic procedures"^{23}.
He then puts forward the hypothesis that class IV characterizes
the automata having universal computation capability. In order to
let this capability emerge, the cells must be able to communicate
and to transmit information. In classes I and II automata cells
are to strongly interdependent to allow a useful information
processing. Class III automata are characterized by a too weak
cells interdependence. Most of automata belong to classes I to
III. They represent 30 over the 32 Wolfram's automata. cellular
automata belonging to class IV are then only to be found in a
minority of cases. The cellular automata that are at the limit
between classes I and II on the one hand, and class III on the
other hand, are the only ones to be capable to deal with
information in a useful way, and therefore are the only
"interesting" ones^{24}. C. Langton was also interested in the
existence of general classification rules of cellular automata but
in a more general way. The difficulty lies into the number of
possible automata. If we consider the only automata with 8 states
and a neighbourhood of 5, there are 8 power 8^{5}, i.e. 8^{32768}
possible universes. Langton decided to classify the cellular
automata depending on a general parameter . The parameter is, in fact, the
probability, within all possible neighbourhood configurations,
that one given configuration should lead to an "active" cell,
i.e. : 1  (number of quiescent transitions/ total number of
transitions) . Using this parameter to build transition rules,
Langton managed to classify cellular automata. For a low value,
cells quickly disappear. If the value is raised over about 0.2,
cyclical or persisting structures appear. Over about 0.3, complex
and unpredictable behaviours appear. Finally, over about 0.5, the
multiplication of structures induces a chaotic behaviour. To a
certain extent the parameter indicates the temperature of the
universe of the cellular automata^{25}. The four following figures show examples of one dimension automata with eight states and a neighbourhood of 5^{26}. =0.1 =0.25 =0.45 =0.8 We then find again Wolfram's
classification, but in a more general framework. According to
Langton, the automata belonging to class IV, those whose
parameter is roughly to be found between 0.3 and 0.5, are those
whose ability to process information is the most important. "(...)
cellular automata capable of performing non trivial computation
 including universal computation  are most likely to be found
in the vicinity of "phase transitions" between order and chaos
(...)"^{27.} J.C. Heudin^{28} uses a parameter () that, in two dimensions cellular automata, corresponds to the number of active neighbours necessary for a cell to remain unchanged. In the game of life, this parameter value is 2. He then redefines automata with four rules :
For=1, the probabilities of rules execution are R4>R3>R2>R1. For = 2, we've got a complete inversion with R1>R2>R3>R4. Beyond 2, the order remains identical, but the rules R2, R3 and R4 are very seldom executed. Heudin then shows a fundamental change in the universe of cellular automata for = 2. It is during this deep modification of the automata properties  this phase transition  that complexity appears : "To appear [complex] needs order and a pinch of chaos. This situation occurs only at the interface of both systems, at the border who leads to chaos."^{29}. With the generalization of cellular automata behaviours, diversity of universal structures or the existence of life, tends to show that the laws of our Universe are precisely at the border between order and chaos. This is what Langton means in the expression : "life at the edge of chaos"^{30}. 22 Wolfram S., Universality and complexity in cellular automata, Physica D, 10:135, 1984. This text is available at : http://www.stephenwolfram.com/publications/articles/ca/84universality/index.html 24 Gutowitz H.A., Langton C.G., Methods for designing Cellular Automata with "Interesting" Behavior, 1994. Available at : http://www.santafe.edu/~hag/interesting/interesting.html. 26 Generated with : http://alife.santafe.edu/cgibin/caweb/lambda.cgi 27 Michell M., Hraber P.T., Crutchfield J., Revisiting the edge of chaos : Evolving Cellular Automate to perform Computations, Santa Fe Institute, Working Paper 9303014, p. 8. This text is available at : http://www.santafe.edu/projects/evca/Papers/revedge.html 28 Heudin J.C., L'évolution..., op. cit., p. 90. Translated by me. 30 Langton C.G., Life at the edge of chaos, Artificial Life II, AddisonWesley, 1991. 
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