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  1. When nomenclature matters: Is the “new paradigm” really a new paradigm for the psychology of reasoning?Markus Knauff & Lupita Estefania Gazzo Castañeda - 2023 - Thinking and Reasoning 29 (3):341-370.
    For most of its history, the psychology of reasoning was dominated by binary extensional logic. The so-called “new paradigm” instead puts subjective degrees of belief center stage, often represented as probabilities. We argue that the “new paradigm” is too vaguely defined and therefore does not allow a clear decision about what falls within its scope and what does not. We also show that there was not one settled theoretical “old” paradigm, before the new developments emerged, and that the alleged new (...)
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  • Introduction to the special issue “Logical perspectives on science and cognition”.Christian J. Feldbacher-Escamilla, Peter Brössel, Alexander Gebharter & Markus Werning - 2020 - Synthese 197 (4):1381-1390.
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  • No-Regret Learning Supports Voters’ Competence.Petr Spelda, Vit Stritecky & John Symons - forthcoming - Social Epistemology:1-17.
    Procedural justifications of democracy emphasize inclusiveness and respect and by doing so come into conflict with instrumental justifications that depend on voters’ competence. This conflict raises questions about jury theorems and makes their standing in democratic theory contested. We show that a type of no-regret learning called meta-induction can help to satisfy the competence assumption without excluding voters or diverse opinion leaders on an a priori basis. Meta-induction assigns weights to opinion leaders based on their past predictive performance to determine (...)
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  • Formal models of source reliability.Christoph Merdes, Momme von Sydow & Ulrike Hahn - 2020 - Synthese 198 (S23):5773-5801.
    The paper introduces, compares and contrasts formal models of source reliability proposed in the epistemology literature, in particular the prominent models of Bovens and Hartmann and Olsson :127–143, 2011). All are Bayesian models seeking to provide normative guidance, yet they differ subtly in assumptions and resulting behavior. Models are evaluated both on conceptual grounds and through simulations, and the relationship between models is clarified. The simulations both show surprising similarities and highlight relevant differences between these models. Most importantly, however, our (...)
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  • Does discussion make crowds any wiser?H. Mercier & N. Claidière - 2022 - Cognition 222 (C):104912.
  • Collectives and Epistemic Rationality.Ulrike Hahn - 2022 - Topics in Cognitive Science 14 (3):602-620.
    Topics in Cognitive Science, Volume 14, Issue 3, Page 602-620, July 2022.
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  • Naïve information aggregation in human social learning.J. -Philipp Fränken, Simon Valentin, Christopher G. Lucas & Neil R. Bramley - 2024 - Cognition 242 (C):105633.
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  • Optimizing group learning: An evolutionary computing approach.Igor Douven - 2019 - Artificial Intelligence 275 (C):235-251.
  • Network effects in a bounded confidence model.Igor Douven & Rainer Hegselmann - 2022 - Studies in History and Philosophy of Science Part A 94 (C):56-71.
    The bounded confidence model has become a popular tool for studying communities of epistemically interacting agents. The model makes the idealizing assumption that all agents always have access to all other agents’ belief states. We draw on resources from network epistemology to do away with this assumption. In the model to be proposed, we impose an explicit communication network on a community, due to which each agent has access to the beliefs of only a selection of other agents. A much-discussed (...)
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  • Mis- and disinformation in a bounded confidence model.Igor Douven & Rainer Hegselmann - 2021 - Artificial Intelligence 291 (C):103415.
  • When philosophy (of science) meets formal methods: a citation analysis of early approaches between research fields.Guido Bonino, Paolo Maffezioli, Eugenio Petrovich & Paolo Tripodi - 2022 - Synthese 200 (2).
    The article investigates what happens when philosophy meets and begins to establish connections with two formal research methods such as game theory and network science. We use citation analysis to identify, among the articles published in Synthese and Philosophy of Science between 1985 and 2021, those that cite the specialistic literature in game theory and network science. Then, we investigate the structure of the two corpora thus identified by bibliographic coupling and divide them into clusters of related papers by automatic (...)
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  • The Wisdom of the Small Crowd: Myside Bias and Group Discussion.Edoardo Baccini, Stephan Hartmann, Rineke Verbrugge & Zoé Christoff - forthcoming - Journal of Artificial Societies and Social Simulation.
    The my-side bias is a well-documented cognitive bias in the evaluation of arguments, in which reasoners in a discussion tend to overvalue arguments that confirm their prior beliefs, while undervaluing arguments that attack their prior beliefs. The first part of this paper develops and justifies a Bayesian model of myside bias at the level of individual reasoning. In the second part, this Bayesian model is implemented in an agent-based model of group discussion among myside-biased agents. The agent-based model is then (...)
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