Self-Modifying-Automaton,
         Chain of Self-Modifying-Automata,
            Self-Programming-Machines.

 

 

The history of life on earth is full of examples of how living things have adapted their responses to the environment, in particular when they are confronted with new conditions. Depending on the context, different names are given to these responses : learning, behaviour, adaptation.

 

·   In the plant word, there is the example of the orchid which can be pollinated because the calyx looks like a female wasp and the corolla exhales a smell identical to a female wasp (Kullenberg, 1956). This way the deluded male wasp carries the pollen from the stamen to the pistil.

·   Among monocellular organisms, paramecia are able to learn and make appropriate reactions (Gelber, 1958).

·   White ants are quickly able to find the shortest route in an extremely complicated man-made-maze when they work as a social group, whereas an isolated insect cannot achieve such a task (Goldberg, 1981).

·   The immune system responds specifically to a new synthetic molecule (Lodish et al.,1995).

·   Many authors consider that the performances of the genome for the evolution of species and that of the nervous system for behaviour, are similar. (Chauvin, 1985)

 

These examples all involve programming without a programmer or performing complicated tasks without human will or intention.

This self programming property seems ubiquitous and must therefore be implemented in various ways : circuits of the nervous system, relationships between social insects, metabolic modifications or exchanges of chemical signals. Due to the diversity of its implementations, the most plausible hypothesis is that the self programming property results from a simple abstract law.

This self programming property gives rise to many arguments :

·   If a living organism is exposed to new conditions, the activation of pre-existing circuits can be invoked in order to explain its response. This kind of hypothesis is often given when the nervous system recovers its functions after a lesion. This argument distances but does not refute the self programming capacity because the activated existing circuit must have been set up previously.

·   When the pertinence of the response is mentioned, how much is real and how much is anthropomorphic illusion ?

There appears to be a paradox : Although living things seem very often to have appropriate responses when new situations arise, it is very difficult to find experiments which can be explained exclusively by the self programming property.

Three such experiments can be cited :

1.   A man permanently wears Dove prisms in front of his eyes. These prisms invert the right and the left side. After any days, the vestibulo ocular reflex is inverted (Gonshor et al., 1976).

2.   In another experiment, the attachment of the internal and external recti muscles of a monkey's eyeball were severed and re-attached in a crossed position so that a contraction of the external rectus would cause the eyeball to turn not outward but inward. When the wound was healed, he was surprised to discover that the two eyeballs still moved together, so that binocular vision was preserved (Marina, 1915).

3.   More recently, another author severed the nerves supplying the flexor and the extensor muscles of a spider monkey and rejoined them in a crossed position. After the nerves had regenerated the animal's arm movements were at first grossly uncoordinated but improved until an essentially normal mode of progression was re-established  (Sperry, 1947).

 

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These results provide one solution to the enigma of self programming machines. The solution given here is a simple abstract law.

1.   In the first publication "Modifiable Automata, Self-modifying-automata"  , (Moulin J-P., 1992), automata which change their internal organisation whenever the external data vary were studied. These automata (self-modifying automata or asm) are deterministic. Their operating rules, the changes of these rules and the initial conditions are randomly chosen once and definitively at the beginning.

 

2.   In the second paper "Very simple models, the modifying automata and chain of self-modifying-automata can explain self properties of the living beings", (Moulin, J-P., 1999), the dynamics of chains of such automata were studied.

 

 

3.   In the paper "Self-programming-machines I", (Moulin, J-P., 2000), the theory of machines which associate two or more asm or chains of asm have been studied. These machines have the self programming property and are called self-programming machines or msp. After a few transient steps, the msp stabilises when it goes indefinitely into a limit cycle of length one (or fixed point). In this case the external value v is the index of a function f such as fv (v)  = v. It stabilises in a self replication process and the pair (fv, v) is self referential.

 

4.   In the paper "Self-programming-machines II" , (Moulin, J-P., 2001), behavior and theory of Network of self-programming-machines driving the hardware of an Ashby homeostat are studied.

 

5.   In the paper "Adaptive properties of living beings: Proposal for a generic mechanism. (Self Programming Machines III)", (Moulin, J-P., 2006), we show that machines with a finite set of inputs, based upon a recurrence, are able to rewrite their internal organization (Self Programming Machines or msp) whenever external conditions vary and have striking properties of adaptation. Msp have similar properties whatever the operation defining the recurrence maybe.
These results bring us to make the following statement: Adaptive properties of living systems can be explained by their ability to rewrite their internal organization whenever external conditions vary under the only assumption that the rewriting mechanism be a deterministic constant recurrence in a finite state set.

 

 

 Finally, Self Programming Machines provide new contributions to :

·         Replicating machines (Von Neumann, 1966; Myhill, 1970; Codd, 1968) and gives a new stability model, namely stability by self replication.

·         The theory of self referential machines (Thatcher, 1965). Many authors, in computer (Ashby, 1961) and natural science (Maturana & Varela, 1981; Zeleny, 1981) consider that self reference is a fundamental concept in comprehension of the mechanisms of perception, behaviour and associations in the brain (Bartlett & Suber, 1987).

·         The theory of learning machines (Anthony, Biggs, 1991).

 

 

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