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  1. Wise Crowds, Clever Meta-Inductivists.Paul D. Thorn - 2015 - In Uskali Mäki, Stéphanie Ruphy, Gerhard Schurz & Ioannis Votsis (eds.), Recent Developments in the Philosophy of Science: EPSA13 Helsinki. Springer. pp. 71-86.
    Formal and empirical work on the Wisdom of Crowds has extolled the virtue of diverse and independent judgment as essential to the maintenance of ‘wise crowds’. In other words, com-munication and imitation among members of a group may have the negative effect of decreasing the aggregate wisdom of the group. In contrast, it is demonstrable that certain meta-inductive methods provide optimal means for predicting unknown events. Such meta-inductive methods are essentially imitative, where the predictions of other agents are imitated to (...)
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  • Truth Tracking Performance of Social Networks: How Connectivity and Clustering Can Make Groups Less Competent.Ulrike Hahn, Jens Ulrik Hansen & Erik J. Olsson - forthcoming - Synthese:1-31.
    Our beliefs and opinions are shaped by others, making our social networks crucial in determining what we believe to be true. Sometimes this is for the good because our peers help us form a more accurate opinion. Sometimes it is for the worse because we are led astray. In this context, we address via agent-based computer simulations the extent to which patterns of connectivity within our social networks affect the likelihood that initially undecided agents in a network converge on a (...)
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  • The Revenge of Ecological Rationality: Strategy-Selection by Meta-Induction Within Changing Environments.Gerhard Schurz & Paul D. Thorn - 2016 - Minds and Machines 26 (1-2):31-59.
    According to the paradigm of adaptive rationality, successful inference and prediction methods tend to be local and frugal. As a complement to work within this paradigm, we investigate the problem of selecting an optimal combination of prediction methods from a given toolbox of such local methods, in the context of changing environments. These selection methods are called meta-inductive strategies, if they are based on the success-records of the toolbox-methods. No absolutely optimal MI strategy exists—a fact that we call the “revenge (...)
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  • Optimisation in a Synchronised Prediction Setting.Christian Feldbacher-Escamilla - 2017 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 48 (3):419-437.
    The standard approach to solve prediction tasks is to apply inductive methods such as, e.g., the straight rule. Such methods are proven to be access-optimal in specific prediction settings, but not in all. Within the optimality-approach of meta-induction, success-based weighted prediction methods are proven to be access-optimal in all possible continuous prediction settings. However, meta-induction fails to be access-optimal in so-called demonic discrete prediction environments where the predicted value is inversely correlated with the true outcome. In this paper the problem (...)
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