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Members: FreeSPS
IEEE Members: $11.00
Non-members: $15.00Length: 01:13:05
09 Jun 2021
This talk explains how agents can learn from dispersed information and solve inference tasks of varying degrees of complexity through localized processing. The presentation also shows how information/misinformation is diffused over graphs, how beliefs are formed, and how the graph topology helps resist/enable manipulation. Examples will be considered in the context of social learning, teamwork, distributed optimization, and adversarial behavior.
