Lower Bounds on the Rate of Learning in Social Networks
e study the rate of convergence of Bayesian learning in social networks. Each individual receives a signal about the underlying state of the world, observes a subset of past actions and chooses one of two possible actions. Our previous work established that when signals generate unbounded likelihood...
| Main Authors: | , , , |
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| Other Authors: | , , , , , , |
| Format: | Article |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers,
2010-11-12T16:10:45Z.
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| Subjects: | |
| Online Access: | Get fulltext |