20220108-MTOA: Accuracy improvement from undertaking additional overlapping tasks follows a law of diminishing returns.

<p>This archive contains the results of a multi-agent simulation experiment [1] carried out with Lazy lavender [2] environment.<br><br>Experiment Label: MTOA-20220108<br><br>Experiment design: Agents improve average accuracy by tackling several tasks.<br><br>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.<br><br>Hypotheses: The higher is the number of carried out tasks, the higher the average accuracy is.<br><br>Detailed information can be found in index.html or notebook.ipynb.<br><br>[1] <a href="https://sake.re/20220108-MTOA">https://sake.re/20220108-MTOA</a><br>[2] <a href="https://gitlab.inria.fr/moex/lazylav/">https://gitlab.inria.fr/moex/lazylav/</a><br><br></p>