Progress for week 9 (2020)

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** Ulike antall individer
** Ulike antall individer
** Ulike Vekt-initialisering, (Disse har gitt best: [-5, 5], [-1,1], [-2,2]) - Kvalitativ og kvantitativ analyse. Se bilder.  
** Ulike Vekt-initialisering, (Disse har gitt best: [-5, 5], [-1,1], [-2,2]) - Kvalitativ og kvantitativ analyse. Se bilder.  
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** Genetisk evolusjon gir veldig rask løsning. (Lokal Optima)
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[[fil:7_markers.png]] [[fil:20_markers.png]] [[fil:28_markers.png]]
[[fil:7_markers.png]] [[fil:20_markers.png]] [[fil:28_markers.png]]
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* Skrevet en god del *
* Skrevet en god del *
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== Wonho ==
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=== Accounting ===
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* Planned experiments and started running them on the cluster
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** 7 cases for 3 different combination of 3 behavior descriptors - 8 runs each makes it ANOVA with df=1 for comparing MBF
 +
** static vs flexible - 8 runs using all features on static controller - compare fitness/distance traveled vs leg length for untrained leg length
 +
** NEAT vs vanila HyperNEAT vs Multi-layered HyperNEAT - 8 runs each using all features
 +
** NS only vs MOEA vs Fitness only - 8 runs each using all features
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* Started writing
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** template setup & structure
 +
** behavioral diversity & MOEA in the background
 +
 +
=== Budget ===
 +
* Start writing implementation
 +
* Implement/test statistical analysis - ANONA/t-Test
 +
* Continue running the experiments. Currently only behavior descriptor test done

Current revision as of 09:49, 27 February 2020

Contents

Nikolai

  • Må lage et bedre mocap armbånd. Det som er nå er ikke rigid nok siden det bruker bare borrelås til å feste markører.
  • Mulig å lese over ~10 sider av implementation? Ønsker å vite om det er helt klart hvordan systemet funker.
  • Visalisering: Se min skjerm.

Tony

  • Eksperimentering *
    • Ulike Fitness funksjoner, (Quantity of Motion, summeringen gir store radianer, manipulatoren beveger for kjapt og urealistisk)
    • Ulike antall Fitness
    • Ulike antall individer
    • Ulike Vekt-initialisering, (Disse har gitt best: [-5, 5], [-1,1], [-2,2]) - Kvalitativ og kvantitativ analyse. Se bilder.
    • Genetisk evolusjon gir veldig rask løsning. (Lokal Optima)


fil:7_markers.png fil:20_markers.png fil:28_markers.png fil:Trained_sum.png fil:Kinetic_energy.png

  • Skrevet en god del *

Wonho

Accounting

  • Planned experiments and started running them on the cluster
    • 7 cases for 3 different combination of 3 behavior descriptors - 8 runs each makes it ANOVA with df=1 for comparing MBF
    • static vs flexible - 8 runs using all features on static controller - compare fitness/distance traveled vs leg length for untrained leg length
    • NEAT vs vanila HyperNEAT vs Multi-layered HyperNEAT - 8 runs each using all features
    • NS only vs MOEA vs Fitness only - 8 runs each using all features
  • Started writing
    • template setup & structure
    • behavioral diversity & MOEA in the background

Budget

  • Start writing implementation
  • Implement/test statistical analysis - ANONA/t-Test
  • Continue running the experiments. Currently only behavior descriptor test done
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