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@inproceedings{Alegre+2022bnaic, | ||
author = {Lucas N. Alegre and Florian Felten and El-Ghazali Talbi and Gr{\'e}goire Danoy and Ann Now{\'e} and Ana L. C. Bazzan and Bruno C. da Silva}, | ||
title = {{MO-Gym}: A Library of Multi-Objective Reinforcement Learning Environments}, | ||
booktitle = {Proceedings of the 34th Benelux Conference on Artificial Intelligence BNAIC/Benelearn 2022}, | ||
year = {2022} | ||
@inproceedings{felten_toolkit_2023, | ||
author = {Felten, Florian and Alegre, Lucas N. and Now{\'e}, Ann and Bazzan, Ana L. C. and Talbi, El Ghazali and Danoy, Gr{\'e}goire and Silva, Bruno C. {\relax da}}, | ||
title = {A Toolkit for Reliable Benchmarking and Research in Multi-Objective Reinforcement Learning}, | ||
booktitle = {Proceedings of the 37th Conference on Neural Information Processing Systems ({NeurIPS} 2023)}, | ||
year = {2023} | ||
} |
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--- | ||
title: "Classic Control" | ||
--- | ||
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# Classic Control | ||
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Multi-objective versions of classical Gymnasium's environments. | ||
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| Env | Obs/Action spaces | Objectives | Description | | ||
|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------|---------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | ||
| [`mo-mountaincar-v0`](https://mo-gymnasium.farama.org/environments/mo-mountaincar/) <br><img src="https://raw.githubusercontent.com/Farama-Foundation/MO-Gymnasium/main/docs/_static/videos/mo-mountaincar.gif" width="200px"> | Continuous / Discrete | `[time_penalty, reverse_penalty, forward_penalty]` | Classic Mountain Car env, but with extra penalties for the forward and reverse actions. From [Vamplew et al. 2011](https://www.researchgate.net/publication/220343783_Empirical_evaluation_methods_for_multiobjective_reinforcement_learning_algorithms). | | ||
| [`mo-mountaincarcontinuous-v0`](https://mo-gymnasium.farama.org/environments/mo-mountaincarcontinuous/) <br><img src="https://raw.githubusercontent.com/Farama-Foundation/MO-Gymnasium/main/docs/_static/videos/mo-mountaincarcontinuous.gif" width="200px"> | Continuous / Continuous | `[time_penalty, fuel_consumption_penalty]` | Continuous Mountain Car env, but with penalties for fuel consumption. | | ||
| [`mo-lunar-lander-v2`](https://mo-gymnasium.farama.org/environments/mo-lunar-lander/) <br><img src="https://raw.githubusercontent.com/Farama-Foundation/MO-Gymnasium/main/docs/_static/videos/mo-lunar-lander.gif" width="200px"> | Continuous / Discrete or Continuous | `[landed, shaped_reward, main_engine_fuel, side_engine_fuel]` | MO version of the `LunarLander-v2` [environment](https://gymnasium.farama.org/environments/box2d/lunar_lander/). Objectives defined similarly as in [Hung et al. 2022](https://openreview.net/forum?id=AwWaBXLIJE). | | ||
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```{toctree} | ||
:hidden: | ||
:glob: | ||
:caption: MO-Gymnasium Environments | ||
./mo-mountaincar | ||
./mo-mountaincarcontinuous | ||
./mo-lunar-lander | ||
./mo-lunar-lander-continuous | ||
``` |
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