20210224-DOLA: Agent adapt ontologies to agree on decision taking (ontology initialisation comparison)

This archive contains the results of a multi-agent simulation experiment [1] carried out with Lazy lavender [2] environment.<br> <br> Experiment Label: 20210224-DOLA<br> <br> Experiment design: Agent adapt ontologies to agree on decision taking (ontology initialisation comparison)<br> <br> Experiment setting: Agents learn decision trees (transformed into ontologies); get income from environment; adapt by splitting their leaf nodes; environment generated from dataset<br> <br> Hypotheses: hypotheses of 20200623-DOLA are still verified for different training algorithms and starting with random ontologies.<br> <br> Detailed information can be found in index.html or notebook.ipynb.<br> <br> [1] https://sake.re/20210224-DOLA<br> [2] https://gitlab.inria.fr/moex/lazylav/