Non-bayesian social learning with uncertain models
© 1991-2012 IEEE. Non-Bayesian social learning theory provides a framework that models distributed inference for a group of agents interacting over a network. Agents iteratively form and communicate beliefs about an unknown state of the world with their neighbors using a learning rule. Existing appr...
Main Authors: | Hare, JZ, Uribe, CA, Kaplan, L, Jadbabaie, A |
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Other Authors: | Massachusetts Institute of Technology. Institute for Data, Systems, and Society |
Format: | Article |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2023
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Online Access: | https://hdl.handle.net/1721.1/148602 |
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