INFORMATION IN COMPLEX SYSTEMS: SEMANTICS, SELFREFERENCE AND CAUSALITY'"

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INFORMATION IN COMPLEX SYSTEMS SEMANTICS,
SELF-REFERENCE AND CAUSALITY."

• D. C. Mikulecky
• Professor Emeritus and Senior Fellow Center for
  the Study of Biological ComplexityVirginia
  Commonwealth University

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WHAT I HOPE TO ACCOMPLISH

• DESCRIBE A NEW FORM OF INFORMATION WHICH CAN BE
  USEFUL IN THE STUDY OF BIOLOGICAL COMPLEXITY
• RELATE THIS FORM OF INFORMATION TO THE FORMALISM
  CALLED RELATIONAL BIOLOGY
• REVIEW THE APPLICATION OF THIS FORMALISM TO THE
  DISTINCTION BETWEEN ORGANISMS AND SIMPLE
  MECHANISMS OR MACHINES

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OUR DEFINITION OF COMPLEXITY

• Complexity is the property of a real world
  system that is manifest in the inability of any
  one formalism being adequate to capture all its
  properties. It requires that we find distinctly
  different ways of interacting with systems.
  Distinctly different in
• the sense that when we make successful
  models, the formal systems needed to describe
  each distinct aspect are NOT
• derivable from each other

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The Mexican sierra fish has "XVII-15-IX" spines
in the dorsal fin. These can easily be counted
... We could, if we wished, describe the sierra
thus "D. XVII-15-IX A. II-15-IX," but we could
see the fish alive and swimming, feel it plunge
against the lines, drag it threshing over the
rail, and even finally eat it. And there is no
reason why either approach should be inaccurate.
Spine-count description need not suffer because
another approach is also used. Perhaps, out of
the two approaches we thought there might emerge
a picture more complete and even more accurate
that either alone could produce.-- John
Steinbeck, novelist, with Edward Ricketts, marine
biologist (1941)
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THE MODELING RELATION A MODEL OF HOW WE MAKE
MODELS
ENCODING
NATURAL SYSTEM
FORMAL SYSTEM
CAUSAL EVENT
IMPLICATION
DECODING
FORMAL SYSTEM
NATURAL SYSTEM
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COMPLEX SYSTEMS VS SIMPLE MECHANISMS

• COMPLEX
• NO LARGEST MODEL
• WHOLE MORE THAN SUM OF PARTS
• CAUSAL RELATIONS RICH AND INTERTWINED
• GENERIC
• ANALYTIC ? SYNTHETIC
• NON-FRAGMENTABLE
• NON-COMPUTABLE
• REAL WORLD

• SIMPLE
• LARGEST MODEL
• WHOLE IS SUM OF PARTS
• CAUSAL RELATIONS DISTINCT
• N0N-GENERIC
• ANALYTIC SYNTHETIC
• FRAGMENTABLE
• COMPUTABLE
• FORMAL SYSTEM

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WHAT IS INFORMATION?

• THERE IS A DIFFERENCE BETWEEN SYNTACTIC AND
  SEMANTIC INFORMATION
• SYNTACTIC INFORMATION IS THE SUBJECT OF
  INFORMATION THEORY IN SCIENCE AND ENGINEERING
• SEMANTIC INFORMATION HAS A VERY DIFFERENT NATURE

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SEMANTIC INFORMATION

• ANSWERS AN INTERROGATIVE (?)
• HAS NO LOGICAL STATUS
• THE ANSWER IS USUALLY AN ADJECTIVE THAT COMES TO
  MODIFY A NOUN
• THE NOUN IS WHAT THE INFORMATION IS ABOUTWHAT IS
  REFERRED TO

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ENTAILMENT SYSTEMS ARISE FROM THE INTERROGATIVE

• WHY?
• WHY X?
• WHAT ENTAILS X?

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THE RELATIONAL DEFINITION OF INFORMATION

• SCIENCE HAS ASKED HOW? AND AS A RESULT HAD A
  MECHANISTIC DEFINITION OF INFORMATION
• THIS HAS INHERENT PROBLEMS SINCE IT CAN NOT DEAL
  WITH SEMANTICS AND SELF-REFERENCE
• WE ASK WHY? AND ARE IMMEDIATELY FORCED TO DEAL
  WITH CAUSAL ENTAILMENT
• THE RESULT IS PROFOUND IN THAT WE NOW DEAL WITH
  THE ESSENCE OF THAT SOMETHING THAT MAKES THE
  WHOLE MORE THAN THE SUM OF ITS PARTS-THE MISSING
  LINK IN REDUCTIONISM
• WE NOW ARE FORCED TO DEAL WITH CLOSED LOOPS OF
  CAUSALITY AND OTHER IMPREDICATIVITIES (SORRY
  RUSSEL)

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THE FOUR BECAUSES WHY A HOUSE?

• MATERIAL THE STUFF ITS MADE OF
• EFFICIENT IT NEEDED A BUILDER
• FORMAL THERE WAS A BLUEPRINT
• FINAL IT HAS A PURPOSE

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THE RELATIONAL APPROACH TO A COMPLEX REALITY

• FOCUS ON THE ORGANIZATION
• DEVELOP A SET OF FUNCTIONAL COMPONENTS WHICH
  CAPTURE THAT ORGANIZATION
• UTILIZE THE CAUSAL RELATIONS RESULTING FROM
  ANSWERING WHY?

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FUNCTIONAL COMPONENTS

• MUST POSSESS ENOUGH IDENTITY TO BE CONSIDERED A
  THING
• MUST BE ABLE TO ACQUIRE PROPERTIES FROM LARGER
  SYSTEMS TO WHICH IT MAY BELONG
• ITS FORMAL IMAGE IS A MAPPING
  f A -----gt B
• THIS INTRODUCES A NEW KIND OF DYNAMICS
  RELATIONAL

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METABOLISM/REPAIR SYSTEMS

• BASED ON INPUT/OUTPUT REPRESENTATIONS OF SYSTEMS
• MORE ABSTRACT
• ALLOW CAUSALITY TO BE REPRESENTED
• LEAD TO NEW INFORMATION
• ARE BASED ON RECOGNITION THAT BUILDING UP AND
  TEARING DOWN ARE PART OF THE LIFE PROCESS

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INPUT/OUTPUT REPRESENTATION NOF A SYSTEM
WHY B? (WHAT ENTAILS B?)
EFFICIENT CAUSE A MAPPING, f
A
B
MATERIAL CAUSE
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THE RELATIONAL REPRESENTATION

• INVOLVES MAPPINGS
• METABOLISM IS f A ? B
• A REPRESENTS METABOLITES WHICH CAN ALSO EXCHANGE
  WITH THE ENVIRONMENT
• B REPRESENTS THE RESULTS OF METABOLISM
• f IS A MAPPING FROM A TO B

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THE CAUSAL RELATIONSHIPS

• A IS THE MATERIAL CAUSE OF B (DOTTED ARROW)
• f IS THE EFFICIENT CAUSE OF B
• OTHER COMPONENTS FOR REPAIR AND REPLICATION COME
  IN BECAUSE THESE COMPONENTS HAVE A FINITE
  LIFETIME CATABOLISM AND ANABOLISM OR TURNOVER

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ROSENS RELATIONAL MODEL OF THE ORGANISM
METABOLISM
f
A
B
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METABOLISM HAS A FINITE LIFETIME. IT CAN BE
EXTENDED BY THE REPAIR OF THE FUNCTIONAL
COMPONENT f

• THE REPAIR OF f MUST BE ENTAILED
• THE MATERIAL CAUSE OF F IS IN THE PRODUCTS OF
  METABOLISM, B
• THE EFFICIENT CAUSE OF f WE WILL CALL ?

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METABOLISM HAS A FINITE LIFETIME. IT CAN BE
EXTENDED BY THE REPAIR OF THE FUNCTIONAL
COMPONENT f
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THE REPAIR FUNCTION CAN BE SHOWN TO BE CLOSELY
RELATED TO A REPLICATION OF FUNCTION IF WE
REQUIRE THAT ? ALSO BE REPAIRED OR REPLACED

• THE MATERIAL CAUSE OF ? IS f . (IT COMES FROM
  AMONG THOSE THINGS THAT ENTAIL METABOLISM).
• CALL THE EFFICIENT CAUSE OF ? ?

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PROVIDING FOR REPAIR OF THE REPAIRER
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THE END OF A POTENTIAL INFINITE REGRESSION
USING CATEGORY THEORY, ROSEN WAS ABLE TO SHOW
THAT GIVEN CONDITIONS EQUIVALENT TO CERTAIN
GENES MAPPING TO CERTAIN PROTEIN ENZYMES, THE
FUNCTIONAL COMPONENT ? IS IDENTICAL WITH B AND,
MORE IMPORTANTLY, THE MAPPING FROM ? TO f IS
ACTUALLY A MAPPING FROM B TO f.
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ROSENS RELATIONAL MODEL OF THE ORGANISM
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ORGANISMS

• ARE COMPLEX SYSTEMS
• ARE CLOSED TO EFFICIENT CAUSE
• ARE AUTOPOIETIC UNITIES

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ROSEN AS BIOLOGYS NEWTON

• NEWTON WAS ABLE TO CLOSE AN INFINITE REGRESSION
  BY FORMULATING F MA
• OVER 300 YEARS OF SCIENCE ARE BUILT ON THIS
• ROSENS CLOSURE OF THE RELATIONAL DIAGRAM SHOWING
  THAT ORGAMNISMS DIFFER FROM MACHINES BY BEING
  CLOSED TO EFFICIENT CAUSE IS AT LEAST AS IMPORTANT