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Lipschitzness is all you need to tame off-policy generative adversarial imitation learning
Despite the recent success of reinforcement learning in various domains, these approaches remain, for the most part, deterringly sensitive to hyper-parameters and are often riddled with essential engineering feats allowing their success. We consider the case of off-policy generative adversarial imit...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9114147/ https://www.ncbi.nlm.nih.gov/pubmed/35602587 http://dx.doi.org/10.1007/s10994-022-06144-5 |