Learning in a black box
We study behavior in repeated interactions when agents have no information about the structure of the underlying game and they cannot observe other agents’ actions or payoffs. Theory shows that even when players have no such information, there are simple payoff-based learning rules that lead to Nash...
| Main Authors: | , , , |
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| Format: | Journal article |
| Published: |
Elsevier
2016
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