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Attention-Based Fault-Tolerant Approach for Multi-Agent Reinforcement Learning Systems
The aim of multi-agent reinforcement learning systems is to provide interacting agents with the ability to collaboratively learn and adapt to the behavior of other agents. Typically, an agent receives its private observations providing a partial view of the true state of the environment. However, in...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8469175/ https://www.ncbi.nlm.nih.gov/pubmed/34573757 http://dx.doi.org/10.3390/e23091133 |