We analyze a social learning model where the agents' utility depends not only on an unknown common component but also … on an unknown idiosyncratic component. Each agent splits a learning budget between the two components. We characterize … the optimal learning decisions and find necessary and sufficient conditions for complete learning. As agents learn from …

disagreement regardless of cognitive ability. Learning about the state of the world has little effect on the evolution of perceived …

The paper analyzes a dynamic model of rational strategic learning in a network. It complements existing literature by … links. This means that in the design of networks there exists a trade-off between the speed of learning and accuracy. …

The paper analyzes a dynamic model of rational strategic learning in a network. It complements existing literature by … that in the design of networks there exists a trade-off between the speed of learning and accuracy. For an incomplete …

collective learning. The present paper provides a summary of this research. …

accuracy is conducive to unstable best-response dynamics. We define the barrier to learning as the minimum level of noise which … the role of strategy restrictions in reducing or amplifying barriers to learning …

We study learning by privately informed forward-looking agents in a simple repeated-action setting of social learning …

learning transfers to new games. Current theories of learning model learning as adjustment in behavior in response to feedback … about outcomes and payoffs and largely ignore the possibility that learning may take place in the absence of such feedback … feedback between plays of the game. However, this previous work demonstrates this "no-feedback" learning using a special game …

the (possibly misspecified) prior belief that her local network is the entire network. We present a tractable learning … rule to implement such locally Bayesian learning: each agent extracts new information using the full history of observed …

of Player 2. We say that beliefs exhibit higher-order learning if the beliefs of Player k about the beliefs of Player k-1 …, higher-order learning fails even after a large number of signals is observed. We argue that this result is driven by base …-rate neglect, heterogeneity in updating processes, and subjects' failure to correctly take learning rules of others into account …