1 / 19

Evolution as Computation

2. Object Complexity. History is important: It is not possible to fully understand an object without considering its formationThe computational view: The formation of any object can be seen in terms of rules acting on initial configurationsThe laws of chemistry and physics constitute rules that ar

whitley
Download Presentation

Evolution as Computation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

    1. 1 Evolution as Computation John Mayfield Department of Genetics, Development, and Cell Biology Iowa State University

    2. 2 Object Complexity History is important: It is not possible to fully understand an object without considering its formation The computational view: The formation of any object can be seen in terms of rules acting on initial configurations The laws of chemistry and physics constitute rules that are followed by physical systems

    3. 3 The existence of some objects can be completely understood in terms of simple laws acting on reasonably probable initial conditions, given local circumstances Examples include: atoms, crystals, rocks, mountains, planets, solar systems, and galaxies Standard physics including nonequilibrium thermodynamics, bifurcation theory, etc. provide tools for understanding such objects

    4. 4 The formation of other objects depends no less on the laws of physics, but also require additional information Examples include: Oak trees, human beings, computers, Mozart symphonies, and industrial corporations

    5. 5 This latter category is characterized by objects whose required initial configurations are wildly improbable These initial configurations only exist because of instructions: they do not occur spontaneously, they are specified

    6. 6 Example: a screwdriver

    7. 7

    8. 8

    9. 9

    10. 10 Characteristics of instructions: Local rules (the laws of physics are universal rules) Usually long and detailed (the laws of physics are short and simple) Constitute purposeful information

    11. 11 To understand instruction-based objects, one must account for the instructions All but the most trivial of instructions are too long (carry too much information) to occur randomly {the probability of 100 bits of information is 2-100, etc.} How does purposeful information come to be?

    12. 12 Generalized theory of evolution At least two ways: Difference equation xt + 1 = s(?xt), where x is the evolving object, t is time, ? is random variation, and s is selection (population is implied). Computation Iterative copying with random change and selection:

    13. 13 Iterated Probabilistic Copying with Selection (IPCS)

    14. 14 The IPCS mechanism [when properly tuned] extracts purposeful information from random events

    15. 15 Examples of systems that employ the IPCS mechanism: Biology (DNA) Agriculture (DNA) Immune system (DNA) Genetic and evolutionary algorithms (computer code) Science and technology (neuronal connectivity patterns, written records) Human learning? (selection of neuronal connectivity patterns)

    16. 16 Claim: All but the most trivial of instructions are ultimately created by the IPCS mechanism For this claim to have credibility, human learning and creativity must be based on the IPCS mechanism

    17. 17 Argument: Human thoughts and knowledge are based in representations consisting of complex neuronal connectivity patterns When faced with the task of learning something never before encountered, the brain has no way to “know” how to create an appropriate connectivity pattern. The only conceivable way to create an appropriate pattern is to begin with existing patterns and evolve new ones by [random] modification of things learned before, and selection.

    18. 18 In philosophy and social science, this idea is known as evolutionary epistemology Carl Popper Donald Campbell Gary Cziko {Without Miracles} In Neuroscience - Neural Darwinism Gerald Edelman

    19. 19 Whence purposeful information? Only two (formally three) possibilities: The environment (back propagation) IPCS (Random search is only a formal possibility, it is too improbable)

More Related