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We study the utility of social learning in a distributed detection model with agents sharing the same goal: a collective decision that optimizes an agreed upon criterion. We show that social learning is helpful in some cases but is provably futile (and thus essentially a distraction) in other cases. Specifically, we consider Bayesian binary hypothesis testing performed by a distributed detection and...
Choosing among alternatives is a basic decision problem faced by people in all aspects of life, whether individually or collectively. Results in cognitive science suggest that people perform approximately Bayes-optimal decision making but that cognitive limitations require the coarse categorization of ensembles of problems rather than the application of optimal decision rules on a problem-by-problem...
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