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Comparing Deep Reinforcement Learning Algorithms’ Ability to Safely Navigate Challenging Waters
Reinforcement Learning (RL) controllers have proved to effectively tackle the dual objectives of path following and collision avoidance. However, finding which RL algorithm setup optimally trades off these two tasks is not necessarily easy. This work proposes a methodology to explore this that lever...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8473616/ https://www.ncbi.nlm.nih.gov/pubmed/34589522 http://dx.doi.org/10.3389/frobt.2021.738113 |