Evolutionary Task Force

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Minutes Converence Call, November 17 - 18 Nov 2011 10:48

Global Task:

  • Each leader writes a paragraph on the progress before Sunday night.

Synchronize the experiments in each subtask so that people do comparable experiments

  • Every group holds a private skype when necesarry
  • Important thing is that experiments are comparable

Subtask 1: Morphogenesis

  • Wenguo has improved his representation to include different connection rotations and heterogeneity
  • Yao: done some experiments in its simulator; working with Ronny to integrate his findings.

Tasks:

  • Michele: Before sunday evening, paragraph summarizing progress.
  • Wenguo: Create mutation, crossover. He will send them to Christopher who will help make them good

Subtask2: Organism Control

  • Until November 30 everyone can use their own simulator
  • By December 15 the solution should be running in Robot3D
  • We postpone the decision until December 15th, as we need to be able to compare them and for that they need to run in the same simulator
  • Everyone needs to be careful that 2 weeks to port your code may be short, so you should look into porting it sooner.

Tasks:

  • Juergen: Before sunday evening, paragraph summarizing progress.
    • Everyone: Send a short text (max 5 - 10 lines) on the progress you made
  • Juergen has an implementation in his own simulator and will implement On-Line On-board evolution there first, and then move on to Robot3D
  • Evert has an implementation in Wiibots and will first implement the inclusion of sensors there, and then move on to Robot3D
  • Florian does not have his own simulator and will work in Robot3D immediately
  • Yao has an implementation in his own simulator and will move toward Robot3D
  • Ronny has an implementation in his own simulator

Subtask3: Internal Reward

  • They will adapt an implementation of the QI to create a Static version of QI.

Tasks:

  • Evert: Implement (he plan to do that before the week-end)
  • There will be an internal discussion after the skype.
  • Evert: Before sunday evening, paragraph summarizing progress.

Subtask 4: Simulator

  • There are still some bugs that Lutz and Vojta are working on.
    • For instance the plugin threads are currently faulty
  • The target platform for now will be Ubuntu 11.04.
    • Any bugs reported should be from this platform
  • Report any bugs to Vojta
  • We will organize a number of tutorials on using Robot3D
    • First tutorial will be somewhere next week.
    • Topics will include
      • Getting, Compiling and Running Robot3D
      • Where to write your controller code, and how to use it in the simulator
      • Some examples
  • Libor and crew have created a component which measures how fast/slow the simulation is compared to real time
  • Several scenarios have been conceptualized and will be implemented
  • First results somewhere next week (Wednesday?)
  • Libor will investigate whether a publication can be made on the simulator
    • The simulator may be a legacy of the project with desirable characteristics

Tasks:

  • Berend: Before sunday evening, paragraph summarizing progress
  • Berend: Confer with Anne and Vojta about bug-reporting and tracking!

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Minutes Converence Call - 10 Nov 2011 15:51

SUB-TASK 1: MORPHOGENESIS

Goal

To test the feasibility of the representation.

Spokesperson

  • Michele (INRIA)

Partners

  • Wenguo: explicit representation, task: create and test evolvability
      • Christopher will help Wenguo with building operators for the explicit representation.
  • Ronny: we have a genome which is evolvable and can build an organism. Tested in simulation.
      • Yao will work with Ronny
  • Inria, implicit representation, task: test evolvability

Other

What a good representation requires, depends on the size of the experiment/organism.

To bootstrap the evolution, we may need an alphabet of shapes; I, H, X, L, T.

  • Ronny: A predefined alphabet may make it hard for evolution to find other shapes.

Initialization phase

For each representation we need to:

  • Know which percentage of individuals is viable, when the genome is initialized randomly
  • How long it takes to complete a shape
  • Define crossover and mutation
  • Know which percentage of offspring viable after crossover/mutation
      • The means for:
      • Explicit: Is the expression well-formed?
      • Implicit: does it converge

The upper-bound on the size of organism is: 4-10.

Procedure

Everyone creates an experiment in their own simulator and sends their plan to Michele. Michele compiles this into a workplan?

SUB-TASK 2: ORGANISM CONTROL PARAMETERS

Goal

The goal is to compare CFG and AHHS and GRN (Yao-yao).

Task: walk, recognize the walls.

Spokeperson

  • Juergen.

Partners

  • Juergen (AHHS)
  • Evert (CPG),
  • Florian (CPG)
  • Yao-yao (GRN)

Procedure

Evert sends an e-mail and organizes things.

SUB-TASK 3: INTERNAL REWARD

Goal

The goal is to re-calibrate the controller when a new shape is created; this recalibration is a nested optimization problem (on-line learning).

In order to optimize, we cannot use a external measure, so what is then criterion?
Options:

  • Distance
  • QI from the traces
  • evolved QI (learning weights on the sensori-motor states) ** this might be too ambitious **

Spokesperson

  • Evert

Partners

  • Evert
  • Michele
  • Christopher

Procedure

Evert sends an e-mail and organizes discussion

SUB-TASK 4: SIMULATOR

Goal

Benchmark the simulator to get a feel for how large an experiment we can run in what time.

Spokesperson

  • Berend

Partners

  • Berend
  • Anne
  • Lutz
  • Libor

Scenario

  • Test#3: loose modules wandering, organisms moving randomly. Empty space with walls.
  • Anne: appropriate sensors;

Other

Christopher: Do we keep all sensors on everywhere, or do we turn off sensors that are useless in simulator?

  • For now we keep them all on, this is probably needed for AHHS anyway.

Berend: We will also simulate computational effort of crossover and mutation, to make the test as realistic as possible.

SCENARIO

  • Procreating requires moving around.
  • Egg receives 2 DNA; then becomes active and recruit others.
  • A cell is an egg or a free cell.
      • Whether a robot is an egg or a free cell is fixed at the start of the simulation
  • An organism has a maximum lifetime (to be set later).
  • An egg does not move

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