zenodoopen
Data and code for the GECCO 2024 paper: "Understanding fitness landscapes in morpho-evolution via local optima networks"
<p>The LON and algorithm run data is available in data/ </p> <p>To run the LON extraction:</p> <p>From gymrem2d-lons/ModularER_2D, run python3 setup.py</p> <p>Direct encoding: python3 lons.py --file direct.cfg</p> <p>LSystem: python3 lons.py --file lsystem.cfg </p> <p>CPPN: python3 lons.py --file cppn.cfg</p> <p> </p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 8
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 0