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“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