Transcript 2011INBIOSAolifant

“The Elephant Lecture”
INBIOSA, Sterling
29 Aug. 2011
Gerard Jagers op Akkerhuis
(the slides are accompanied by notes!!)
What is the problem?
 Existing attempts at integration seem not to
solve “hard” problems (INBIOSA)
Why is this a problem?
 Progress of science is blocked
Can this challenge be met?
 Is there an elephant in the room?
But where to search for an
“invisible”elephant?…
Use four straight lines
and connect all dots
without lifting the pen from the paper
Maybe the elephant hides outside our view?
hierarchy
fractals
neural
networks
modularity
AI
genetic
algorithms
semiotics
sociology
complexity
genetics
evolution
quantum
physics
autopoiesis
modelling
chemistry
biophysics
robotics
life
What is the “right”
angle to find the
elephant?
Biosphere
An example of a conventional approach to system
organization
Ecosystem
Community
Population
Organisms
Organ systems
How is this constructed?
Organs
Tissues
Cells
Organelles
Miller:
Living
systems
Molecules
Atoms
Fundamental particles
Biosphere
Ecosystem
What have we learned
from our example?
Are we maybe “cheating”
by fitting a straight line
through more-dimensional data?
Community
Population
Organisms
Organ systems
Organs
Tissues
Cells
Organelles
Molecules
Atoms
Fundamental particles
Biosphere
The steps in detail:
Let’s consider
the separate
Ecosystem
operator
Community
hierarchy
Tissues
Population
Organisms
Multicellulars
Organs
Biosphere
Organ systems
Organ
systems
Ecosystem
Organs
Organs
Community
Tissues
Population
Cells
Endosymbionts
Organ
systems
Cells (bacteria sl)
Organelles
Organelles
Molecules
Molecules
Atoms
Atoms
Fundamental
particles
Fundamental
particles
UPWARD:
Operators
OUTWARD:
Interaction
systems
Multicellulars
Endosymbionts
Cells (bacteria sl)
Tissues
INWARD:
Internal
differentiations
Organs
Organ
systems
can be
improved
Miller:
Living systems
Molecules
Organs
Organ
systems
Atoms
Hadrons
Organelles
Fundamental
particles
The operator hierarchy depends on
‘closure’:
• distinguishes a particle from its environment
(Heylighen)
Closure as the operator hierarchy uses it, is caused by:
a new cyclic shape and
a new cyclic process,
which together create the first-next level of selforganization
For example:
}
2. Interaction systems
1. Operators
(first-next
possible
closure)
3. Internal differentiation
The operator hierarchy
SAE
SCI
HMI
multi-particle
hypercycle
interface
 closure dimensions
predictions
sensors
euk. multicell.
neuron cycle
eukaryote cell
multicellular
cell
cell membrane
autocatalysis
molecule
atom
electron shell
Mind that grey bars
represent intermediate
system states required to
create the operators
hadron
atom
nucleus
confinement
quark-gluon
interaction
particles
 closure levels
memon
The operator hierarchy
Interesting theory, but what is it good for?
Examples of applications….
Application 1: Life (not ‘living’!) =
all operators from the level of the cell and up
- Not relevant: Metabolism
- Not relevant: Reproduction
- Not only relevant: First cell
+ Hierarchical definition
+ Basic structures: operators
+ No circularity
Application 2: an additional level
in the ‘tree of life’
Memons
multicellulars
unicellular
endosymbionts
bacteria sl
Application 3:
The future of evolution
As soon as we provide these
things, which we regard as
“machines”, with the
appropriate neural structure,
they fit to the operator
hierarchy and are life
Summary:
A tool for
analysis
Closure
An integration framework
across disciplines
Operator
hierarchy
Life
Memon
Three dimensions
for hierarchy
In other words…
Future
The operator hierarchy
An “invisible” elephant in the room
Thank you for your attention
Gerard Jagers op Akkerhuis
[email protected] and www.hypercycle.nl