Naive Learning Through Probability Matching
Proceedings of the 2019 ACM Conference on Economics and Computation, pp. 553-553, 2019.
information aggregation learning in networks non-bayesian learning social networks
We analyze boundedly rational updating in a repeated interaction network model with binary states and actions. We decompose the updating procedure into a deterministic stationary Markov belief updating component inspired by DeGroot updating and pair it with a random probability matching strategy that assigns probabilities to the actions g...More
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