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Nash Equilibrium of Social-Learning Agents in a Restless Multiarmed Bandit Game
We study a simple model for social-learning agents in a restless multiarmed bandit (rMAB). The bandit has one good arm that changes to a bad one with a certain probability. Each agent stochastically selects one of the two methods, random search (individual learning) or copying information from other...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5434024/ https://www.ncbi.nlm.nih.gov/pubmed/28512339 http://dx.doi.org/10.1038/s41598-017-01750-z |