Explainable deep reinforcement learning: state of the art and challenges

GA Vouros - ACM Computing Surveys, 2022 - dl.acm.org
Interpretability, explainability, and transparency are key issues to introducing artificial
intelligence methods in many critical domains. This is important due to ethical concerns and …
被引用次数：78 相关文章

Explainable Deep Reinforcement Learning: State of the Art and Challenges

GA Vouros - arXiv preprint arXiv:2301.09937, 2023 - arxiv.org
Interpretability, explainability and transparency are key issues to introducing Artificial
Intelligence methods in many critical domains: This is important due to ethical concerns and …

Explainable Deep Reinforcement Learning: State of the Art and Challenges

GA Vouros - arXiv e-prints, 2023 - ui.adsabs.harvard.edu
Interpretability, explainability and transparency are key issues to introducing Artificial
Intelligence methods in many critical domains: This is important due to ethical concerns and …
[PDF] archive.org

[PDF][PDF] Explainable Deep Reinforcement Learning: State of the Art and Challenges

GA VOUROS - 2022 - scholar.archive.org
Interpretability, explainability and transparency are key issues to introducing Artiicial
Intelligence methods in many critical domains: This is important due to ethical concerns and …