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  1. Argumentation-induced rational issue polarisation.Felix Kopecky - 2024 - Philosophical Studies 181 (1):83-107.
    Computational models have shown how polarisation can rise among deliberating agents as they approximate epistemic rationality. This paper provides further support for the thesis that polarisation can rise under condition of epistemic rationality, but it does not depend on limitations that extant models rely on, such as memory restrictions or biased evaluation of other agents’ testimony. Instead, deliberation is modelled through agents’ purposeful introduction of arguments and their rational reactions to introductions of others. This process induces polarisation dynamics on its (...)
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  • Optimizing group learning: An evolutionary computing approach.Igor Douven - 2019 - Artificial Intelligence 275 (C):235-251.
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  • Argumentative landscapes: the function of models in social epistemology.N. Emrah Aydinonat, Samuli Reijula & Petri Ylikoski - 2021 - Synthese 199 (1-2):369-395.
    We argue that the appraisal of models in social epistemology requires conceiving of them as argumentative devices, taking into account the argumentative context and adopting a family-of-models perspective. We draw up such an account and show how it makes it easier to see the value and limits of the use of models in social epistemology. To illustrate our points, we document and explicate the argumentative role of epistemic landscape models in social epistemology and highlight their limitations. We also claim that (...)
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  • Coherence and correspondence in the network dynamics of belief suites.Patrick Grim, Andrew Modell, Nicholas Breslin, Jasmine Mcnenny, Irina Mondescu, Kyle Finnegan, Robert Olsen, Chanyu An & Alexander Fedder - 2017 - Episteme 14 (2):233-253.
    Coherence and correspondence are classical contenders as theories of truth. In this paper we examine them instead as interacting factors in the dynamics of belief across epistemic networks. We construct an agent-based model of network contact in which agents are characterized not in terms of single beliefs but in terms of internal belief suites. Individuals update elements of their belief suites on input from other agents in order both to maximize internal belief coherence and to incorporate ‘trickled in’ elements of (...)
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  • Anchoring in Deliberations.Stephan Hartmann & Soroush Rafiee Rad - 2020 - Erkenntnis 85:1041-1069.
    Deliberation is a standard procedure to make decisions in not too large groups. It has the advantage that the group members can learn from each other and that, at the end, often a consensus emerges that everybody endorses. But a deliberation procedure also has a number of disadvantages. E.g., what consensus is reached usually depends on the order in which the different group members speak. More specifically, the group member who speaks first often has an unproportionally high impact on the (...)
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  • Explaining the Success of Induction.Igor Douven - 2023 - British Journal for the Philosophy of Science 74 (2):381-404.
    It is undeniable that inductive reasoning has brought us much good. At least since Hume, however, philosophers have wondered how to justify our reliance on induction. In important recent work, Schurz points out that philosophers have been wrongly assuming that justifying induction is tantamount to showing induction to be reliable. According to him, to justify our reliance on induction, it is enough to show that induction is optimal. His optimality approach consists of two steps: an analytic argument for meta-induction (that (...)
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  • Truth Approximation, Social Epistemology, and Opinion Dynamics.Igor Douven & Christoph Kelp - 2011 - Erkenntnis (2):271-283.
    This paper highlights some connections between work on truth approximation and work in social epistemology, in particular work on peer disagreement. In some of the literature on truth approximation, questions have been addressed concerning the efficiency of research strategies for approximating the truth. So far, social aspects of research strategies have not received any attention in this context. Recent findings in the field of opinion dynamics suggest that this is a mistake. How scientists exchange and take into account information about (...)
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  • Pandemics and flexible lockdowns: In praise of agent-based modeling.Igor Douven - 2023 - European Journal for Philosophy of Science 13 (3):1-27.
    Philosophers have recently questioned the methodological status of agent-based modeling. Meanwhile, this methodology has been central to various studies of the COVID-19 pandemic. Few agent-based COVID-19 models are accessible to philosophers for inspection or experimentation. We make available a package for modeling the COVID-19 pandemic and similar pandemics and give an impression of what can be achieved with it. In particular, it is shown that by coupling an agent-based model to a standard optimizer we are able to identify strategies for (...)
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  • 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.
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  • Inference to the Best Explanation versus Bayes’s Rule in a Social Setting.Igor Douven & Sylvia Wenmackers - 2017 - British Journal for the Philosophy of Science 68 (2).
    This article compares inference to the best explanation with Bayes’s rule in a social setting, specifically, in the context of a variant of the Hegselmann–Krause model in which agents not only update their belief states on the basis of evidence they receive directly from the world, but also take into account the belief states of their fellow agents. So far, the update rules mentioned have been studied only in an individualistic setting, and it is known that in such a setting (...)
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  • Meta-induction in epistemic networks and the social spread of knowledge.Gerhard Schurz - 2012 - Episteme 9 (2):151-170.
    Indicators of the reliability of informants are essential for social learning in a society that is initially dominated by ignorance or superstition. Such reliability indicators should be based on meta-induction over records of truth-success. This is the major claim of this paper, and it is supported in two steps. One needs a non-circular justification of the method of meta-induction, as compared to other learning methods. An approach to this problem has been developed in earlier papers and is reported in section (...)
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  • Highly idealized models of scientific inquiry as conceptual systems.Renne Pesonen - 2024 - European Journal for Philosophy of Science 14 (3):1-22.
    The social epistemology of science has adopted agent-based computer simulations as one of its core methods for investigating the dynamics of scientific inquiry. The epistemic status of these highly idealized models is currently under active debate in which they are often associated either with predictive or the argumentative functions. These two functions roughly correspond to interpreting simulations as virtual experiments or formalized thought experiments, respectively. This paper advances the argumentative account of modeling by proposing that models serve as a means (...)
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  • The ecological rationality of explanatory reasoning.Igor Douven - 2020 - Studies in History and Philosophy of Science Part A 79 (C):1-14.
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  • How group members contribute to group performance: Evidence from agent-based simulations.Igor Douven - 2016 - Behavioral and Brain Sciences 39.
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