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taking an (irreversible) action. We define \textit{asymptotic learning} as the fraction of agents taking the correct action … converging to one as a society grows large. Under truthful communication, we show that asymptotic learning occurs if (and under … ``information hubs'', which receive and distribute a large amount of information. Asymptotic learning therefore requires information …
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significantly, deep learning approaches require massive datasets. We know that the theory and algorithms have been around for quite …
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In resource based learning settings learners have to cope with a multitude of resources. One big challenge for learners … and related tools with regard to learning scenarios. This paper focuses on presenting a knowledge modeling approach based … supporting exchange of knowledge. Furthermore a proof-of-concept is described. -- Resource based learning ; knowledge networks …
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Under the bounded rationality assumption, a principal rarely provides an optimal contract to an agent. Learning from … others is one way to improve such a contract. This paper studies the efficiency of social network learning (SNL) in the … learning efficiency and posits several summative hypotheses. The simulation results validate these hypotheses, and we discuss …
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We study a dynamic game in which short-run players repeatedly play a symmetric, strictly supermodular game whose payoff depends on a fixed unknown state of nature. Each short-run player inherits the beliefs of his immediate predecessor in addition to observing the actions of the players in his...
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