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Tim (and Chris): Have developed a boolean network in NetLogo:
Tim (and Chris): Have developed a boolean network in NetLogo:
* [[http://www.phrogstar.de/files/rbn-explorer.nlogo RBN Explorer]]
* [[http://www.phrogstar.de/files/rbn-explorer.nlogo RBN Explorer]]
* [[http://www.phrogstar.de/files/rbn-explorer.nlogo RBN Generator]] - use this program to generate files for the Failure/Healing Program
* [[http://www.phrogstar.de/files/rbn-generator.nlogo RBN Generator]] - use this program to generate files for the Failure/Healing Program
* [[http://www.phrogstar.de/files/rbn-explorer.nlogo RBN Failure/Healing Program]]
* [[http://www.phrogstar.de/files/rbn-failure.nlogo RBN Failure/Healing Program]]


Next steps: define the input nodes to the network and set of output nodes to represent a function. Suggestion at last meeting: Use the configuration of the whole network as the input. Alternate suggestion: Is there a way to have input as a fixed set of nodes so that the boolean network can itself work as a module (this would make the network analogous to the brain and the inputs analogous to the sensory neurons).
Next steps: define the input nodes to the network and set of output nodes to represent a function. Suggestion at last meeting: Use the configuration of the whole network as the input. Alternate suggestion: Is there a way to have input as a fixed set of nodes so that the boolean network can itself work as a module (this would make the network analogous to the brain and the inputs analogous to the sensory neurons).

Revision as of 17:05, 24 July 2007

CSSS Santa Fe 2007

Title

An investigation into healing strategies for boolean networks (?) [Perhaps lexical networks as well - see further below]

Can be seen as the boolean approach of Learning & the aging brain --Amelie

though boolean networks seems a good choice, I think we should still keep an open mind whether we want to use boolean networks only (useful for modelling brain, circuits etc where a global function is computed by the network.) or a network of intelligent nodes (like computers useful for peer-to-peer, distributed, real computer networks etc). -- Amitabh

Next Meetings

Week 3 - Thursday, 4:30pm - Great Hall (by Chris)

Week 2 - Thursday, 12:30 - Great Hall (by Chris)

Week 2 - Tuesday, 12:30 - Great Hall (by Chris)

Members

  1. Alex Healing (alexhealing (at) gmail.com)
  2. Amelie Veron
  3. Sayan -- See suggested project on healing in lexical networks at this page: Lexical Networks
  4. Christian Darabos
  5. Amitabh Trehan
  6. nathan menke
  7. Tim Johann
  8. ...


Overview

Simple

  1. Random Boolean Network
  2. Evolve network parameters (boolean function, connections, ...)
  3. Select n best networks
  4. Apply different healing strategies to each n network and compare

Evolved-Resilience Network

  1. Random Boolean Network
  2. Evolve with failures / insertions
  3. Select n best networks
  4. Apply different healing strategies


Healing Strategies

  • Re-evolve whole network
  • Local healing / Directed evolution
    • Static re-evolution around failure point
      • Breadth-first
      • Depth-first
    • Dynamic expansion of re-evolution


Types of failure


Still to decide

  • Simulation environment - Java? : NetLogo?
  • Stochasisity / non-determinism?
  • Boolean functions, etc...

Planning and Progress

( Suggested: Please enter the aspect of the project you are working on and with whom and your suggestions for coordination)

Tim (and Chris): Have developed a boolean network in NetLogo:

Next steps: define the input nodes to the network and set of output nodes to represent a function. Suggestion at last meeting: Use the configuration of the whole network as the input. Alternate suggestion: Is there a way to have input as a fixed set of nodes so that the boolean network can itself work as a module (this would make the network analogous to the brain and the inputs analogous to the sensory neurons).

Attempt local (and other suggested healings) and study healing performance? (by Amitabh)


Background Reading

...