### Infomorphism

 Editor Francisco  Salto francisco.salto@unileon.es Incorporated contributions Salto(29/07/09) Usage domain transdisciplinary, situation theory Type concept French Infomorphisme German Infomorphismus

The mathematical concept of morphism tries to produce an image of a set  that captures its structure. The notion of infomorphism generalizes and extends this idea by means of defining certain homomorphism among structures supporting infons. The concept emerged originally in situation semantics and it has been applied in distinct contexts.

Any set A includes all elements or tokens defining a family R of relations on A. Let us call relational structure A the set A with these relations. Let A, B respectively be relational structures <A,R> y <B,S>. Taken with benevolence, an homomorphism from A to B is defined as any function f from A into B such that:  If  R(a1…an), then S(f(a1)…f(an)). B is then an homomorphic image of A.

Consider now the specific relational structure which we may call classificatory relational structure A, taken as the result of classifying the elements or tokens of A by means of a set ΣA of types. For example, the set of tokens: {a, a, a} corresponds to a unique type a. We write xëAy to say that the token x instantiates the type y. Barwise y Seligman (1997) called classifications such classificatory structures A=<A,αA,A>, where A is the grounding token set, ΣA  the set of individual types and A the relation of being an instance of.

Let  A and B both be classificatory structures:

An infomorphism i relating A y B consists in a pair of functions f+ (from αA to αB) and ¯ (from B to A) such that, for every type α of A and every token b de B:

f+(b) A α <═> bBf ¯(a).

Schematically:

As an homomorphism preserves structure, so an infomorphism preserves the instantiation relation, among sets that can be quite distinct, but informationally analogous.

In the references (Devlin, Gunji) you may find relevant examples of infomorphisms.

References
• BARWISE, J. & SELIGMAN, J. (1997). Information Flow. The Logic of Distributed Systems. Cambridge: C.U.P.
• BREMER, M. & COHNITZ, D. (2004). Information and Information Flow. Frankfurt: Ontos Verlag.
• DEVLIN, K. (2001). The Mathematics of Information. Lecture 4: Introduction to Channel Theory. ESSLLI 2001, Helsinki, Finland
• GUNJI, Y.P., TAKAHASHI, T. & AONO, M. (2004) "Dynamical infomorphism: form of endo-perspective". Chaos, Solitrons & Fractals 22, 1077-1101.
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Francisco Salto (29-07-2009)

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