a new book; special issue on emergence; preprint availab

[Kampis Gyorgy]

                     ANNOUNCEMENTS

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1. a new book
2. a Special Issue on emergence
3. preprint available

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1. the book

				George Kampis 	

SELF-MODIFYING SYSTEMS IN BIOLOGY AND COGNITIVE SCIENCE:
a New Framework for Dynamics, Information and Complexity

Pergamon, Oxford-New York, March 1991, 546pp with 96 Figures


About the book:

The main theme of the book is the possibility of generating
information by a recursive self-modification and self-
redefinition in systems. 

The book offers technical discussions of a variety of systems
(Turing machines, input-output systems, synergetic systems,
connectionist networks, nonlinear dynamic systems, etc.) to
contrast them with the systems capable of self-modification. 

What in the book are characterized as 'simple systems' involve a
fixed definition of their internal modes of operations, with
variables, parts, categories, etc. invariant. Such systems can be
represented by single schemes, like computational models of the
above kind. A relevant observation concerning model schemes is
that any scheme grasps but one facet of material structure, and
hence to every model there belongs a complexity excluded by it.
In other words, to every simple system there belongs a complex
one that is implicit. 

Self-modifying systems are 'complex' in the sense that they are
characterized by the author as ones capable to access an
implicate material complexity and turn it into the information
carrying variables of a process. An example for such a system
would be a tape recorder which spontaneously accesses new modes
of information processing (e.g. bits represented as knots on the
tape). A thesis discussed in the book is that unlike current
technical systems, many natural systems know how to do that
trick, and make it their principle of functioning. 

The book develops the mathematics, philosophy and methodology for
dealing with such systems, and explains how they work. A
constructive theory of models is offered, with which the modeling
of systems can be examined in terms of algorithmic information
theory. This makes possible a novel treatment of various old
issues like causation and determinism, symbolic and nonsymbolic
systems, the origin of system complexity, and, finally, the
notion of information. The book introduces technical concepts
such as information sets, encoding languages, material
implications, supports, and reading frames, to develop these
topics, and a class of systems called 'component-systems', to
give examples for self-modifying systems. As an application, it
is discussed how the latter can be applied to understand aspects
of evolution and cognition.