The novelty of our model is to combine models of collective action on networks with models of social learning. Agents …

We study social learning in a social network setting where agents receive independent noisy signals about the truth …

We study the impact of bots on social learning in a social network setting. Regular agents receive independent noisy …

Different theories of expectation formation and learning usually yield different outcomes for realized market prices in … dynamic models. The purpose of this paper is to investigate expectation formation and learning in a controlled experimental …

macroeconomic models in which agents are boundedly rational and use an adaptive learning rule to form expectations of the endogenous … estimate it empirically. Two prominent learning algorithms are considered, namely constant gain and decreasing gain learning …. For each of the two learning rules, the analysis proceeds in two stages. First, the paper derives the asymptotic …

, Simpson, and Gelman(2018), to a setting where dynamic learning occurs about features of predictive densities of possibly … misspecified models. This improves the averaging process of good and bad model forecasts. We summarise how this learning is done in … connection with machine learning. We illustrate our suggestion using results from Ba̧stürk, Borowska, Grassi, Hoogerheide, and …

estimation of the parameters in an auxiliary model. The learning scheme employed by the agents belongs to the class of stochastic …