Cargando…
Intrinsic fluctuations of reinforcement learning promote cooperation
In this work, we ask for and answer what makes classical temporal-difference reinforcement learning with [Formula: see text] -greedy strategies cooperative. Cooperating in social dilemma situations is vital for animals, humans, and machines. While evolutionary theory revealed a range of mechanisms p...
Autores principales: | Barfuss, Wolfram, Meylahn, Janusz M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9873645/ https://www.ncbi.nlm.nih.gov/pubmed/36693872 http://dx.doi.org/10.1038/s41598-023-27672-7 |
Ejemplares similares
-
Population Fluctuation Promotes Cooperation in Networks
por: Miller, Steve, et al.
Publicado: (2015) -
Multiagent cooperation and competition with deep reinforcement learning
por: Tampuu, Ardi, et al.
Publicado: (2017) -
Scaffolding cooperation in human groups with deep reinforcement learning
por: McKee, Kevin R., et al.
Publicado: (2023) -
Resonant tunneling of fluctuation Cooper pairs
por: Galda, Alexey, et al.
Publicado: (2015) -
Two-Community Noisy Kuramoto Model Suggests Mechanism for Splitting in the Suprachiasmatic Nucleus
por: Rohling, Jos H. T., et al.
Publicado: (2020)