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.

Experiment Label: 20210224-DOLA

Experiment design: Agent adapt ontologies to agree on decision taking (ontology initialisation comparison)

Experiment setting: Agents learn decision trees (transformed into ontologies); get income from environment; adapt by splitting their leaf nodes; environment generated from dataset

Hypotheses: hypotheses of 20200623-DOLA are still verified for different training algorithms and starting with random ontologies.

Detailed information can be found in index.html or notebook.ipynb.

[1] https://sake.re/20210224-DOLA
[2] https://gitlab.inria.fr/moex/lazylav/