“The Elephant Lecture”

1. “The Elephant Lecture” INBIOSA, Sterling 29 Aug. 2011 Gerard Jagers op Akkerhuis (the slides are accompanied by notes!!)

2. 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?…

3. Use four straight lines and connect all dots without lifting the pen from the paper Maybe the elephant hides outside our view?

4. neural networks AI genetic algorithms hierarchy fractals modularity semiotics sociology complexity genetics evolution autopoiesis quantum physics modelling life robotics chemistry biophysics

6. What is the “right” angle to find the elephant?

7. 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

8. Biosphere Ecosystem What have we learned from our example? Community Population Are we maybe “cheating” by fitting a straight line through more-dimensional data? Organisms Organ systems Organs Tissues Cells Organelles Molecules Atoms Fundamental particles

9. Biosphere Let’s consider the separate steps in detail: The operator hierarchy Ecosystem Community Tissues Population Organs Organisms Multicellulars Organ systems Organ systems Biosphere Organs Organs Ecosystem Endosymbionts Organ systems Community Tissues Population Organelles Cells (bacteria sl) Cells Organelles Molecules Molecules Atoms Atoms Fundamental particles Fundamental particles

10. UPWARD: Operators Biosphere Ecosystem Community Population OUTWARD: Interaction systems Multicellulars Endosymbionts Cells (bacteria sl) Tissues Molecules Organs Organs Atoms Organ systems Organ systems INWARD: Internal differentiations Hadrons Organelles Fundamental particles can be improved Miller: Living systems

11. 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: } cyclic shape > cyclic process >

12. Interaction systems • Operators (first-next possible closure) • Internal differentiation

13. SAE SCI HMI multi-particle hypercycle interface memon sensors euk. multicell. neuron cycle eukaryote cell multicellular cell cell membrane autocatalysis molecule atom electron shell atom nucleus hadron confinement quark-gluon interaction particles The operator hierarchy  closure dimensions predictions  closure levels Mind that grey bars represent intermediate system states required to create the operators

14. The operator hierarchy Interesting theory, but what is it good for? Examples of applications….

15. 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

16. Application 2: an additional level in the ‘tree of life’ Memons multicellulars unicellular endosymbionts bacteria sl

17. Application 3: Thefuture 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

18. An integration framework across disciplines Summary: A tool for analysis Operator hierarchy Life Closure Memon Future In other words… Three dimensions for hierarchy

19. The operator hierarchy An “invisible” elephant in the room Thank you for your attentionGerard Jagers op Akkerhuisgerard.jagers@wur.nl and www.hypercycle.nl