20230505-MTOA: Multitasking agents improve their average and maximum accuracy when tasks overlap.

This archive contains the results of a multi-agent simulation experiment [1] carried out with Lazy lavender [2] environment.Experiment Label: 20230505-MTOAExperiment design: Agents specialize by accepting or not to play a task.Experiment setting: Agents are trained with respect to different tasks and then coordinate upon acting on them. Each time they disagree, one agent adapts its knowledge with respect to the current task.Hypotheses: Agents will improve their accuracy more on tasks they choose to play.Detailed information can be found in index.html or notebook.ipynb.[1] https://sake.re/20230505-MTOA[2] https://gitlab.inria.fr/moex/lazylav/