Introduction Directory UMM :Data Elmu:jurnal:B:Biosystems:Vol55.Issue1-3.2000:

BioSystems 55 2000 159 – 171 A diffuse biosemiotic model for cell-to-tissue computational closure Ron Cottam , Willy Ranson, Roger Vounckx The E6olutionary Processing Group EVOL , Laboratory for Micro and Opto Electronics LAMI , VUB Di6ision of the Inter-Uni6ersity Micro Electronics Center IMEC , The Uni6ersity of Brussels VUB , Pleinlaan 2 , 1050 Brussels, Belgium Abstract The adoption of diffuse rationality creates a practical bridge between biosemiotics and computation in formulating local-to-global self-consistent criteria for cellular-to-tissue interfacing and for the emergence of life and consciousness. Nature is always complex, the more so at biological membranic inter-scalar interfaces. We present an evolutionary model of the relationship between autonomy and dependence across scales, and describe the implications of its alternating complex – rational – complex nature. © 2000 Elsevier Science Ireland Ltd. All rights reserved. Keywords : Diffuse biosemiotics; Complementary rationalities; Cross-scale correlation; Semiotic stabilization; Cell-to-tissue closure www.elsevier.comlocatebiosystems

1. Introduction

The description of natural processes as forms of computation goes far beyond the attribution to evolution and change of a conventional mathe- matical algorithmic character. Algorithmic ap- proaches not only fail to be complete Go¨del, 1962, but also somewhat paradoxically fail to describe successfully the rationally incomplete na- ture of much of natural change as we experience it. To be successful, an overall self-consistent de- scription of biological relationships must be grounded in a framework which encompasses far more than any con6entional formal system. This is not to say that a general form of evolution cannot be captured by formalism, but that a major change in the nature of the formalisms we employ will be necessary to do so. Cell-to-tissue closure is most certainly non-al- gorithmic in nature, and consequently it is not directly accessible to computer modeling, at least not currently through the use of conventional homogeneous logic or conventional computers. We believe, however, that it is describable as being computational in nature, in a far wider sense of meaning of the word ‘computation’. Im- provement in precisely this aspect of computa- tional accessibility, through the development of a suitable inhomogeneous hierarchical rationality, is a main thrust of the present work. Conventional science is founded on paradigms derived mainly from the realm of physics rather than that of biology, although there is a growing movement Corresponding author. Tel.fax: + 32-2-6292933. E-mail address : evoletro.vub.ac.be R. Cottam 0303-264700 - see front matter © 2000 Elsevier Science Ireland Ltd. All rights reserved. PII: S 0 3 0 3 - 2 6 4 7 9 9 0 0 0 9 4 - 5 away from the presupposition that biology can be simplistically reduced to physics and chem- istry. Concurrently, since a number of decades, there is a developing realization that much can be gained by introducing the formalizations and implications of semiotics into biological descrip- tions, with the consequent emphasis not only on syntactical but also on semantic aspects of or- ganisms and their sub-systems. The aim of the investigation reported in this paper is the extension of evolutionary biosemi- otic approaches to all aspects of our surround- ings in a unified manner, from the animate to the inanimate, and beyond. The specific target of the paper is to describe a self-consistent framework within which the presence of evolu- tion and complexity mirror their natural appear- ances, and where the closure of computational relationships between cell, tissue and organism may be confidently grounded. Rather than di- viding the scheme conventionally into a system- atically-coupled hierarchy of rationality, paradigm and model, we integrate all these facets into a single complexly-coupled hierarchi- cal integrated real-to-model ‘structure’ which transcends Rosen’s 1991 Mikulecky, 1999a modeling relation. All of nature may be complex Mikulecky, 1999b, but we find that the simple models which we derive in ‘explaining’ natural phenomena are direct matches to those simple entities which nature itself formulates as stabiliz- ing local approximates to a complex universal background phase space.

2. Initial criteria