Week 4 Report


Further improvement on explicitly representation of organism
Implemented a simple genetic algorithm on evolving organism shapes;
next: better design of fitness function and parameter tuning
Code is updated in repository https://ipvs.informatik.uni-stuttgart.de/software/repos/software/controller/uwe/og/


Improving the Genome structure. Installing the Robot3d simulator. Taking into account viability constraints, see below.


Excused for medical reasons


Extension from deterministic to stochastic cellular automata.
Curves (average max. size vs number fitness evaluations; average nb of distinct shapes vs number of fitness evaluations) attached. All result files available at: http://www.lri.fr/~sebag/_symb314


a single constraint of morpho viability: dock on a single side at the same time
discussion about which fitness function: size of new shape.


Define primitives: virtual class Egg; primitive Egg.Create_Organism()
Preliminary validation setting: Wenguo's (Player): to collect indicators below.
Use by partners:
* we might need shortcuts: Each free robot knows where the eggs are, and if they recruit; and it goes there directly.


  • Size of genome
  • Properties of the mapping (when implicit)
      • Deterministic / stochastic
      • Ratio phenotypes/genotype
      • Controllability: find genome for a given phenotype
  • Initialization
      • Viability: between 3 and 10 cells
      • Percentage of viable phenotypes from random genotypes
  • Variation operators
      • Number of distinct shapes produced along evolution, from random init, vs number of fitness evaluations.
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