Nash Equilibrium of Social-Learning Agents in a Restless Multiarmed Bandit Game
Abstract 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 f...
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| Auteurs principaux: | , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2017
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| Accès en ligne: | https://doaj.org/article/9e250b018c12484b82a9e9fc551d2d65 |
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