Essentially, all models are wrong, but some are useful. - George Box

See ExtendedLayeredModel as its more complete version


lowest to highest complexity, increase of managed units (each unit on the layer N is constituted of an organization of units from N-1). Note that this does not imply reductionism or downward causality, only different levels of analysis with a continuum of interactions between them.

  1. information :
    1. information creation (following a discussion with Sylvain1)
      1. epistemology
        1. evolutionary epistemology
          1. CAEE Seedea:Research.Research
  2. physics :
  3. chemistry :
  4. biology* :
  5. neurology :
  6. psychology :
  7. sociology :
  8. politics :


  • Stability is insured by statistical law, or the law of big numbers, i.e. each level doesn't "collapse" to the previous one and keeps "emergent properties" thanks to statistical stability.
  • I hope that with own definitions like Biology#Cell that have a shared algorithmic and network view point and use more than 1 layer I will gradually gain a better overall understanding
    • for example could this definition also be used in conjunction with models like the trophic web?

Biology separation

biological entity have model of selves and reproduction

  • (nomology, hard sciences, Godel theorem, recursion) distinction
  • rule systems (cf AIWProposal and recently related read material) as equivalent to laws in lower than biology layers
  • exchange of information for energy (cf own definition of "life")
  • consider everything that is bellow that level as extended homeostasis
    • metaphor of the house electrically closing its roller window shutter in the evening, just like the eyelids of its inhabitants

Inspired by

Hervé Le Guyader's remark "La biologie va se trouver a l'interface d'une serie de sciences dures que ce soit la biochimie, la biophysique, la description de toutes ses molecules, la mathematisation de la genetique des populations, etc, etc, et bien evidement tout une partie qui est contingente, qui correspond a l'histoire. C'est cette interaction entre les deux qui est tellement riche." during Les enjeux de la science, Continent Science, France Culture December 2010

"To model an object is to possess it" Picasso


  1. In Knots: emergent knowledge systems and the Inka khipu by Katie King, Narrative and Emergent Knowledge 2005
    • "collapsing levels as you dynamically shift focus for varying amounts of time and attention"
    • in February 2010 in Saint-Maur about what was my own strategy to reach my own objective
      • saying that in computer science we learned to handle several layers of abstractions, a classical example being Wikipedia:OSI model, but also how you have source code, design patterns, frameworks, virtual machine, compiled code, processor instructions and that to program but also to debug you have to navigate easilly in and between those layers so somehow also collapsing them

To do

  1. add "missing" layers
    1. mathematics? philosophy? geography? climatology?
  2. transform to a proper list template rather that doing it manually
    1. only provide the ordered layers name then get the list of categories
  3. add an easy-tagging recipe for my wiki, like a droplist option to append tags to the current page instead of manually editing each
  4. created MyBeliefs?
  5. cartographies
    1. earliers maps of scientific fields
  6. integrate the CS specific Programming#EntireStack
    1. itself should integrate Programming#HardwareSpecific
  7. transform to a practical table including for each layer
    1. results, cookbooks/tools/models, content/books/videos/references
      1. in order to generate new results/tools/content in other layers
  8. develop layer transparency
    1. you master a topic when you can use its model transparently without having to consciously explore it to draw conclusions but rather directly use it for a purpose
      1. as if it was a black box, an abstract tool, that if you wanted you could have looked into but didn't need to
    2. e.g. knowing the Internet infrastructure, the OSI layer, the software behavior, enough to just start a second HTTP query before the first is finished because it is more efficient in that situation but without consciously consider all the implications
  9. if growth in complexity in biological organisms is done by copying functions from other organisms directly or by using them through coupling then gradually removing irrelevant functions to waste less energy, could it also apply at the social level?
    • i.e. can a society of organisms decide for the energetic purpose of optimization to strip out of their constituent properties?
  10. write an abstract layer including the interfaces with other layers
    • based on layer transparency and coupling, consequently interfacing layers through equivalents of interdependency loops
  11. use examples to produce visualization of shifts in layers during an analysis or presentation
  12. list and associate models (networked or not, cf Cognition#HistoryOfDominantCognitiveModels) per layer, e.g.
    1. Wikipedia:Genome
    2. Wikipedia:Connectome
    3. Wikipedia:Interactome
    4. Wikipedia:Proteome
    5. Internet as a meta-network with layers as network not merely technical computer networks
    6. Seedea:Utopiahanalysis/UniNetVerseVisu
    7. use Seedea:Research/PhylogeneticFlowProgramming to parse through it and provide an interface through
      1. add discussion with Paola

To categorize

(:pagelist link=Category.UncategorizedBook list=normal fmt=simple:)

  • others book that
    • have no individual page or that
    • have page made before the Template with UncategorizedBook was done (cf earlier attempts to list those in the to do section)
  • see also all the existing tags (:pagelist group=Category list=normal fmt=#title:) thanks to PmWiki:Categories