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Threshold Phenomena in Epistemic Networks

In Proceedings, AAAI Fall Symposium on Complex Adaptive Systems and the Threshold Effect. AAAI Press (2006)

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  1. A Mid-Level Approach to Modeling Scientific Communities.Audrey Harnagel - 2019 - Studies in History and Philosophy of Science Part A 76:49-59.
    This paper provides an account of mid-level models, which calibrate highly theoretical agent-based models of scientific communities by incorporating empirical information from real-world systems. As a result, these models more closely correspond with real-world communities, and are better suited for informing policy decisions than extant how-possibly models. I provide an exemplar of a mid-level model of science funding allocation that incorporates bibliometric data from scientific publications and data generated from empirical studies of peer review into an epistemic landscape model. The (...)
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  • Method Pluralism, Method Mismatch, & Method Bias.Adrian Currie & Shahar Avin - 2019 - Philosophers' Imprint 19.
    Pluralism about scientific method is more-or-less accepted, but the consequences have yet to be drawn out. Scientists adopt different methods in response to different epistemic situations: depending on the system they are interested in, the resources at their disposal, and so forth. If it is right that different methods are appropriate in different situations, then mismatches between methods and situations are possible. This is most likely to occur due to method bias: when we prefer a particular kind of method, despite (...)
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  • Some Lessons From Simulations of Scientific Disagreements.Dunja Šešelja - 2019 - Synthese 198 (Suppl 25):6143-6158.
    This paper examines lessons obtained by means of simulations in the form of agent-based models about the norms that are to guide disagreeing scientists. I focus on two types of epistemic and methodological norms: norms that guide one’s attitude towards one’s own theory, and norms that guide one’s attitude towards the opponent’s theory. Concerning I look into ABMs that have been designed to examine the context of peer disagreement. Here I challenge the conclusion that the given ABMs provide a support (...)
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  • Formal Models of Scientific Inquiry in a Social Context: An Introduction.Dunja Šešelja, Christian Straßer & AnneMarie Borg - 2020 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 51 (2):211-217.
    Formal models of scientific inquiry, aimed at capturing socio-epistemic aspects underlying the process of scientific research, have become an important method in formal social epistemology and philosophy of science. In this introduction to the special issue we provide a historical overview of the development of formal models of this kind and analyze their methodological contributions to discussions in philosophy of science. In particular, we show that their significance consists in different forms of ‘methodological iteration’ whereby the models initiate new lines (...)
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  • Exploring Scientific Inquiry Via: Agent-Based Modelling.Dunja Šešelja - 2021 - Perspectives on Science 29 (4):537-557.
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  • Centralised Funding and the Division of Cognitive Labour.Shahar Avin - unknown
    Project selection by funding bodies directly influences the division of cognitive labour in scientific communities. I present a novel adaptation of an existing agent-based model of scientific research, in which a central funding body selects from proposed projects located on an epistemic landscape. I simulate four different selection strategies: selection based on a god's-eye perspective of project significance, selection based on past success, selection based on past funding, and random selection. Results show the size of the landscape matters: on small (...)
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  • Modelling the Truth of Scientific Beliefs with Cultural Evolutionary Theory.Krist Vaesen & Wybo Houkes - 2014 - Synthese 191 (1).
    Evolutionary anthropologists and archaeologists have been considerably successful in modelling the cumulative evolution of culture, of technological skills and knowledge in particular. Recently, one of these models has been introduced in the philosophy of science by De Cruz and De Smedt (Philos Stud 157:411–429, 2012), in an attempt to demonstrate that scientists may collectively come to hold more truth-approximating beliefs, despite the cognitive biases which they individually are known to be subject to. Here we identify a major shortcoming in that (...)
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  • Scientific Networks on Data Landscapes: Question Difficulty, Epistemic Success, and Convergence.Patrick Grim, Daniel J. Singer, Steven Fisher, Aaron Bramson, William J. Berger, Christopher Reade, Carissa Flocken & Adam Sales - 2013 - Episteme 10 (4):441-464.
    A scientific community can be modeled as a collection of epistemic agents attempting to answer questions, in part by communicating about their hypotheses and results. We can treat the pathways of scientific communication as a network. When we do, it becomes clear that the interaction between the structure of the network and the nature of the question under investigation affects epistemic desiderata, including accuracy and speed to community consensus. Here we build on previous work, both our own and others’, in (...)
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  • Modeling Epistemology: Examples and Analysis in Computational Philosophy of Science.Patrick Grim - 2019 - In A. Del Barrio, C. J. Lynch, F. J. Barros & X. Hu (eds.), IEEE SpringSim Proceedings 2019. IEEE. pp. 1-12.
    What structure of scientific communication and cooperation, between what kinds of investigators, is best positioned to lead us to the truth? Against an outline of standard philosophical characteristics and a recent turn to social epistemology, this paper surveys highlights within two strands of computational philosophy of science that attempt to work toward an answer to this question. Both strands emerge from abstract rational choice theory and the analytic tradition in philosophy of science rather than postmodern sociology of science. The first (...)
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  • Diversity, Ability, and Expertise in Epistemic Communities.Patrick Grim, Daniel J. Singer, Aaron Bramson, Bennett Holman, Sean McGeehan & William J. Berger - 2019 - Philosophy of Science 86 (1):98-123.
    The Hong and Page ‘diversity trumps ability’ result has been used to argue for the more general claim that a diverse set of agents is epistemically superior to a comparable group of experts. Here we extend Hong and Page’s model to landscapes of different degrees of randomness and demonstrate the sensitivity of the ‘diversity trumps ability’ result. This analysis offers a more nuanced picture of how diversity, ability, and expertise may relate. Although models of this sort can indeed be suggestive (...)
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  • Germs, Genes, and Memes: Functional and Fitness Dynamics on Information Networks.Patrick Grim, Daniel J. Singer, Christopher Reade & Stephen Fisher - 2015 - Philosophy of Science 82:219-243.
    It is widely accepted that the way information transfers across networks depends importantly on the structure of the network. Here, we show that the mechanism of information transfer is crucial: in many respects the effect of the specific transfer mechanism swamps network effects. Results are demonstrated in terms of three different types of transfer mechanism: germs, genes, and memes. With an emphasis on the specific case of transfer between sub-networks, we explore both the dynamics of each of these across networks (...)
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