(soon)
3/8/2004 10:12 AM
There seems to be a fundamental
difference we need to acknowledge first between natural physical (including biological)
systems, engineered physical systems
and theoretical systems . Theoretical (scientific) systems are based on
logic since they must be reproducible, analyzable and predictable. A specific
logic system necessarily is restricted to a single logic domain, defined by an
axiom (theory), from which deductions and decompositions can be made using
logic rules. As long as theoretical systems are isolated (abstracted) from
interactions with other theoretical systems (i.e. other logic domains set by
different theories) as their environment, they remain predictable. Based on
such theoretical systems, physical machines can be constructed as engineered
physical systems. Such an isolated, mono-logic system I would call a
“mechanism”.
Physical systems in general cannot
be completely isolated from their environment, however. As a result, many (n-)
logic domains interact with a given physical system as forces or logics. The
behaviour of a physical system therefore cannot be described as a pure
mechanism except in an idealized way. This still allows us to build engineered
physical systems, but it also means that all engineered physical systems
eventually age, break down and deteriorate. They are never fully analyzable, predictable or not even exactly reproducible. I
suggest to call systems where different logic domains intersect as “complex”. { + } Complexity
cannot be fully analyzed (logically decomposed into all interacting logic
domains) because even finite numbers of domains create infinite interacting
effects. We can only “intuitively” understand complex systems and describe them
in a reductionist way by reducing the number of domains and effects.
Biological systems can be seen as
natural physical systems which make use of this “polylogic” condition as
bio-chemical reactor or engine that provides them with certain neg-entropic
self-dynamics instead of the only re-active and dynamics of engineered physical
systems and entropic dynamics of non-living natural physical systems.
I see two fundamental approaches to
the problem:
-
When using
only one domain of logic in the description (mapping) of a complex system, we
reduce it qualitatively to an idealized mechanism or theoretical systems.
-
Using more
than one domain of logic in a description requires new architectures of mapping several logic domains into a domain,
where the integration does not lead to a qualitative reduction (under one axiom
as root of one domain), but respects and differentiates independent logic
domains. Such an architecture has been called “rhizomatic”, “polylogic” or
“poly-hierarchic”.
The latter approach is also
reductionist in that it must limit the number of domains to whatever is
physically computable. But this reductionism is quantitative, not qualitative. The resulting system is still
complex, not just complicated.
Since logic is the only computable
approach available to us, this is probably the closest we can come in mapping
and abstracting complex systems. Human thinking as a combination of intuition
and logic seems to be using a similar approach: Intuition allows us to see
patterns as result of complex interactions and to produce (usually by analogy)
theories and axioms that establish logic domains where logic deduction can then
be applied.
Our dominant (Western) cultures
have emphasized logic and have failed to develop methods to combine logic
domains to allow systematic or even artificial intuition based on the patterns
of intersecting logic domains. This has nevertheless enabled us to build
extremely complicated mechanisms and industrialize our economies. While Eastern
cultures have based their thinking more on intuition and polylogic (Yin and
Yang), they have – probably for that reason and at least for a long time - not
been able to exploit as well the potential of mechanism and engineered physical
systems. But as can be seen in medicine and other fields, both approaches have
merit and can deliver solutions, especially when dealing with complexity.
In a globalized future where
complexity and polylogic interactions become more and more vital not only in
natural sciences and engineering, but also in social relations, a combined
approach could be valuable.
There are now new methods and tools
available to map complexity into polylogic architectures and thus combine the
two worlds of complexity and mechanism. This will allow us to build complex
engineered physical systems that share some of the fundamental characteristics
of natural physical systems. Cognition is one of these characteristics.
Peter
Krieg