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Drive <- Strategical Epistemology <- Bibliography <- EpistemicModel <- Result (+ Visualization + BackEnd + PhylogeneticFlowProgramming) <- Experiments (+ Datasets )
"<-" = Backtrack Learning
Non pas des verites acquises mais l'idee d'une recherche libre
on the walls of the College de France
CAEE : Standing efficiently on the shoulders of giants
Inspired by an IRC discussion:
21:16 <Leviathan7> well no one goes to church for good reasons we all know they tha
21:17 <UtopiahGHML> going there for a lack of a better belief to hold to.
21:17 <UtopiahGHML> which makes perfect sense
21:19 <Leviathan7> that's how our biological system work we only do what benefits us, Love is the only thing that breaks this law
21:21 <UtopiahGHML> (on a sidenode, that just gave me an idea for an EE motto : standing *efficiently* on the shoulder of giants, or sth like that)
21:21 <Leviathan7> Or looking upon the giants.. idk
21:22 <UtopiahGHML> http://en.wikipedia.org/wiki/Standing_on_the_shoulders_of_giants
21:23 <Leviathan7> beautiful painting. yes we are the dwarfs
21:29 <UtopiahGHML> I guess Im ok being even smaller if I can get a spot higher to see further away ;)
- computer assisted evolutionary epistemology (C.A.E.E.)
- collaborative p2p epistemology (see stigmergylive from TheLab)
- Why doing this research and writing it down in a wiki?
- Because it allows to structure thought on the long term and hopefully avoid wasteful dispersion and deficit of attention. Having a long term focus, even if not successful regarding its initial goal should still be in itself a positive process.
- Why a wiki in particular?
- see WhyWikis but overall to be allowed to organize thoughts while keeping a certain flexibility.
- Why this domain?
- Why this particular hypothesis?
- because so far it seems to be the more logical and fruitful one, cf also Motivation
Survival leads to problem solving
Living organisms are pressured toward the same goal, maintaining homeostasis. They all developed solutions to do so. Consequently, life with and without intelligence is a continuous problem solving mechanism. Evolution and its result, the phylogeny tree, is the biological exploration to this constraint in a changing environment.
phylogeny is the biological answer over time to the question "How to survive in the current environment?"
- my hypothesis is that this is an exploration of the solution space
- the implication is that this is part of a larger phylogeny answering the same question (this should be visualized by putting the current phylogeny within a bigger one)
- the consequence is that culture, technology, etc are further exploratio to this larger solution space but that the same evolutionary still aply and thus that the techniques related to phylogeny should be generalized
Creativity is Physical
According to my notes on Programming the Universe
Evolution of natural creative strategies
- creativity/diversity engines in nature in a chronological order
- not a tree of biological species nor a tree of their solutions to competition
- inspired by
Evolution of errors
- evolution of
- bias (micro)
- cognitive error (meso)
- conceptual framework (macro)
See also Jonathan's reference to Max Weber.
Meta-phylogeny, evolution of "trees"
- organize and potentialy synthesize
- making it "portable/mind sizable" is the first step in being able to use it
- detect potential correlation
- evaluate priorities
- detect the pace of evolution
- to produce estimation for the potential next change
- gathering data on constructed phylogenies
- first biological phylogenies
- Phylogeny.fr Robust Phylogenetic Analysis For The Non-Specialist
- Inferring Phylogenies by Joseph Felsenstein, Sinauer Associates 2004
- propositions in Research.Visualization
- Evolutionary of natural creative strategies
- Evolution of errors
- gathered ones based on my interests
Directions for future research
- define this to live a unique life
- philosophical basis
- biological evolution : Darwin
- universal darwinism : Dawkins
- evolutionary epistemology : Campbell/Munz/Cziko/...
- process = finding a pattern, generalizing, applying to another domain
- epistemology in general
- actors (individuals, institutions, ...)
- processes (learning, discovering, transforming, transferring, mashing up, locking, ...)
- mapping the domain
- theoretical foundations
- mathematical framework
- recursive structures/patterns (fractals, ...)
- computational framework
- AI, machine learning, ...
- use technical framework to facilitate innovation
- assisting tools trough computational scientometrics
- Current related applications
- clarify the "book" structure
- make it "dynamic", a book that can be read but also "executed"
- either directly with code (better) or at least with workflows
- each chapter having its associated code
- SemanticWiki book?
- in the same way that you can't apply Heisenberg uncertainty principle everywhere, you can't apply evolutionary principles everywhere
- so explain cleary what does make it more likely to effectively apply to creativity
- evolution being "pervasive" + "natural" solution that created our existing "solution finder"
cf The Research Roadmap, Avoid common pitfalls on the research journey (mostly) by Brian Whitworth
way too broad...
Introducing the work in a much broader context, those renown work provide fundamentals that will be used to go further. They must be clarified first in order to discuss the topic with a common understanding of the problem at hand.
Should be organized in key disciplines around a map of concepts.
- cognitive scaffolding by A. Clark
- affordance by J. Gibson
- recursive self-improvement by C. Darwin, R. Kurzweil
- Ontogenesis/Autopoeisis by Francisco Varela
- Without Miracles : Cultural Knowledge as the Evolution of Tradition, Technology, and Science by Gary Cziko
- Karl Popper evolutionary epistemological equation
- Fractal Universe : A Pictorial Hypothesis by Colin Hillfractal universe and Fractal cosmology, it relates to the usage or appearance of fractals in the study of the universe or cosmos. (very broad, to introduce carefuly)
- Selection Theory Bibliography by Gary A. Cziko and Donald T. Campbell
Labs with the state of the art
imprecise, lack of direct examples
Those are too related to general learning instead of real epistemological advancement (about machine supported learning but NOT directly linked with creativity).
This protocol serve as a way to provide a way to falsify the theory and prove that so far, it is coherent.
Environment : classrooms on innovation
- test m classrooms with and n-m without
- during a period of time during which the interactions of groups are impossible to remove comparison on exchange of methods/tools
- evaluate their result by someone who does not know who uses what (double blind, eventually using OSEO or another "official" method)
- establish if there is a correlation link betwheen the tool used and the result produced
Environment : online innovation platform
- random blind and verification thanks to perfect randomization eventually inspired by Google Image Game and CMU reCAPTCHA (except that it seems they don't use random user matching result here, to check)
Links for official supporting institutions
Papers to read
See also PersonalInformationStream for current readings
- The Venturesome Economy: How Innovation Sustains Prosperity in a More Connected World by Amar Bhide, Princeton University Press, Autumn 2008
Creative destruction Joseph Schumpeter popularized and used the term to describe the process of transformation that accompanies radical innovation.
- The Upside of Down - The Argument by Thomas Homer-Dixon
How We Evolve by Benjamin Phelan for Seed Magazine (October 7, 2008)
- Interesting opening on Lahn Lab work from the Department of Human Genetics of The University of Chicago, especially regarding potential gene pools difference of pace according to environmental pressure and thus still happening today
- IEI's Patented Creativity Machine Paradigm, Result so far are private. Ability to integrate it? (sounds very coherent with C.A.E.E.) Doesn't look like Frank Rosenblatt (inventor of the Perceptron), not even Stephen Thaler from IEI who supposedely combined the Perceptron with the Imagitron)
Stigmergic Collaboration: A Theoretical Framework for Mass Collaboration by Dr Mark Alan Elliott (2007)
PhD thesis, Centre for Ideas, Victorian College of the Arts, University of Melbourne. (read only
the first third, cf online notes)
Stigmergic collaboration - Meta Collab
Heylighen F. (2007). Why is Open Access Development so Successful? Stigmergic organization and the economics of information, in: B. Lutterbeck, M. Baerwolff & R. A. Gehring (eds.), Open Source Jahrbuch 2007, Lehmanns Media, 2007, p. 165-180.
Rodriguez, M.A., Collectively Generated Model of the World, Collective Intelligence: Creating a Prosperous World at Peace, eds. M. Tovey, pages 261-264, EIN Press, ISBN:09715-6616X, Oakton, Virgina, November 2007.
- Collective Decision Making Systems (CDMS) project to eventually go further than InTrade.net (theoretically interesting but much less popular)
Ant Attack, BBC Natural World, 2006
Ants - Natures Secret Power, Wolfgang Thaler, 2004
- Stigmergic epistemology, stigmergic cognition by Leslie Marsh, Christian Onof for Cognitive Research System, June 2007
A game-theoretic interpretation of Marcel Mauss' ‘The gift’ by Robert Rider for The Social Science Journal, Volume 35, Issue 2, 1998, Pages 203-212
- Notes on The evolution of cooperation : Axelrod, Robert
- Darwin's Blind Spot: Evolution Beyond Natural Selection by Frank Ryan November 3, 2003
- to check against Without Miracle by Gary Cziko
- Out of Control - Chapter 5: Coevolution by Kevin Kelly, 1995
- MIT Center for Collective Intelligence
- How can people and computers be connected so that—collectively—they act more intelligently than any individuals, groups, or computers have ever done before? (seems very similar to our stated goal in CoEvolution)
Notes de lecture Du mode d'existence des objets techniques par Gilbert Simondon, 1958
- The Interactive Nature of Computing: Refuting the Strong Church-Turing Thesis by Dina Goldin, Peter Wegner, Brown University, 2007
Algorithmic information theory
- Programming the Universe by Seth Lloyd, 2006 (ISBN 978-1-4000-4092-6, read only
the first third)
Physical Limits of Computing by Michael P. Frank, 2002
- Market Intelligence for Innovation & Product Life-Cycle - Case Examples for Global Intelligence Alliance, April 2008
- Including development on biomimicry
- lower priority
- even lower...
Useful for keywords in searches but also to get funding (example of nanotech vs. classical chemistry terms).
- open innovation
- continuous innovation
- check with
- personal work
- Ideonomy : the dream of Patrick Gunkel about his website. (not that relevant)
- Is Anything Ever New? Considering Emergence by James P. Crutchfield
- Smart World by Richard Ogle (and its "Further Reading")
- Intelligence amplification/Man-Computer Symbiosis
- Bot participation to collaborative environment : Intelligence in Wikipedia by Daniel S. Weld for Google, November the 11th 2008
- especially the feedback loop @33:00
- Creativity techniques "There is an analogy between many creativity techniques and methods of evolutionary computation."
- On writting
- Evolutionary epistemology
- Evolutionary tools "curiosities"
- Folie et créativité for Les Années lumière on Radio-Canada.ca - Découverte
- Cziko's The Things We Do (read, notes to add)
- Strangely he never mentions enaction or work by Varela!
- A Guide for Writing Scientific Papers for studies and research in. Micro- and nanotechnologies at. Vestfold University College that mentions From Research to Manuscript - A Guide to Scientific Writing by Michael Jay Katz, Springer 2009, 2nd edition
- Epistemology, scientific method, and statistics from University of Ottawa - Bio 4118 – Applied Biostatistics, 2002
- Methodspace "home of the Research Methods community from across the world" by SAGE
- myExperiment find, use and share scientific workflows and other Research Objects
- myGrid » Taverna automation of experimental methods through the use of a number of services, including Web Services.
- The "P vs. NP" Problem: Efficient Computation, Internet Security, and the Limits of Human Knowledge by Avi Wigderson, Institute for Advanced Study 2008
- "If P=NP, we have fast automatic finder. <<Creativity>> can be efficiently automated. " min36
- So, you know what’s important? by Daniel Lemire, March 2010
- "greedy algorithms can be pretty good. They can certainly beat 5-year plans"
- Knowledge The illustrated guide to a Ph.D. Made by Matt Might