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Peter Brössel
Ruhr-Universität Bochum
  1. The Problem of Measure Sensitivity Redux.Peter Brössel - 2013 - Philosophy of Science 80 (3):378-397.
    Fitelson (1999) demonstrates that the validity of various arguments within Bayesian confirmation theory depends on which confirmation measure is adopted. The present paper adds to the results set out in Fitelson (1999), expanding on them in two principal respects. First, it considers more confirmation measures. Second, it shows that there are important arguments within Bayesian confirmation theory and that there is no confirmation measure that renders them all valid. Finally, the paper reviews the ramifications that this "strengthened problem of measure (...)
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  2. Evidence of Evidence as Higher Order Evidence.Anna-Maria A. Eder & Peter Brössel - 2019 - In Mattias Skipper & Asbjørn Steglich-Petersen (eds.), Higher-Order Evidence: New Essays. Oxford University Press. pp. 62-83.
    In everyday life and in science we acquire evidence of evidence and based on this new evidence we often change our epistemic states. An assumption underlying such practice is that the following EEE Slogan is correct: 'evidence of evidence is evidence' (Feldman 2007, p. 208). We suggest that evidence of evidence is best understood as higher-order evidence about the epistemic state of agents. In order to model evidence of evidence we introduce a new powerful framework for modelling epistemic states, Dyadic (...)
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  3. Bayesian Confirmation: A Means with No End.Peter Brössel & Franz Huber - 2015 - British Journal for the Philosophy of Science 66 (4):737-749.
    Any theory of confirmation must answer the following question: what is the purpose of its conception of confirmation for scientific inquiry? In this article, we argue that no Bayesian conception of confirmation can be used for its primary intended purpose, which we take to be making a claim about how worthy of belief various hypotheses are. Then we consider a different use to which Bayesian confirmation might be put, namely, determining the epistemic value of experimental outcomes, and thus to decide (...)
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  4.  51
    No Knowledge Required.Kevin Reuter & Peter Brössel - 2018 - Episteme 16 (3):303-321.
    Assertions are the centre of gravity in social epistemology. They are the vehicles we use to exchange information within scientific groups and society as a whole. It is therefore essential to determine under which conditions we are permitted to make an assertion. In this paper we argue and provide empirical evidence for the view that the norm of assertion is justified belief: truth or even knowledge are not required. Our results challenge the knowledge account advocated by, e.g. Williamson (1996), in (...)
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  5. How to Resolve Doxastic Disagreement.Peter Brössel & Anna-Maria A. Eder - 2014 - Synthese 191 (11):2359-2381.
    How should an agent revise her epistemic state in the light of doxastic disagreement? The problems associated with answering this question arise under the assumption that an agent’s epistemic state is best represented by her degree of belief function alone. We argue that for modeling cases of doxastic disagreement an agent’s epistemic state is best represented by her confirmation commitments and the evidence available to her. Finally, we argue that given this position it is possible to provide an adequate answer (...)
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  6. On the Role of Explanatory and Systematic Power in Scientific Reasoning.Peter Brössel - 2015 - Synthese 192 (12):3877-3913.
    The paper investigates measures of explanatory power and how to define the inference schema “Inference to the Best Explanation”. It argues that these measures can also be used to quantify the systematic power of a hypothesis and the inference schema “Inference to the Best Systematization” is defined. It demonstrates that systematic power is a fruitful criterion for theory choice and IBS is truth-conducive. It also shows that even radical Bayesians must admit that systemic power is an integral component of Bayesian (...)
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  7.  8
    10. Referees for Philosophy of Science Referees for Philosophy of Science (Pp. 479-482).Justin Garson, Yasha Rohwer, Collin Rice, Matteo Colombo, Peter Brössel, Davide Rizza, Simon M. Huttegger, Richard Healey, Alyssa Ney & Kathryn Phillips - 2013 - Philosophy of Science 80 (3):334-355.
  8.  51
    Rational Relations Between Perception and Belief: The Case of Color.Peter Brössel - 2017 - Review of Philosophy and Psychology 8 (4):721-741.
    The present paper investigates the first step of rational belief acquisition. It, thus, focuses on justificatory relations between perceptual experiences and perceptual beliefs, and between their contents, respectively. In particular, the paper aims at outlining how it is possible to reason from the content of perceptual experiences to the content of perceptual beliefs. The paper thereby approaches this aim by combining a formal epistemology perspective with an eye towards recent advances in philosophy of cognition. Furthermore the paper restricts its focus, (...)
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  9.  68
    Assessing Theories: The Coherentist Approach.Peter Brössel - 2014 - Erkenntnis 79 (3):593-623.
    In this paper we show that the coherence measures of Olsson (J Philos 94:246–272, 2002), Shogenji (Log Anal 59:338–345, 1999), and Fitelson (Log Anal 63:194–199, 2003) satisfy the two most important adequacy requirements for the purpose of assessing theories. Following Hempel (Synthese 12:439–469, 1960), Levi (Gambling with truth, New York, A. A. Knopf, 1967), and recently Huber (Synthese 161:89–118, 2008) we require, as minimal or necessary conditions, that adequate assessment functions favor true theories over false theories and true and informative (...)
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  10.  29
    Learning Concepts: A Learning-Theoretic Solution to the Complex-First Paradox.Nina Laura Poth & Peter Brössel - 2020 - Philosophy of Science 87 (1):135-151.
    Children acquire complex concepts like DOG earlier than simple concepts like BROWN, even though our best neuroscientific theories suggest that learning the former is harder than learning the latter and, thus, should take more time (Werning2010). This is the Complex- First Paradox. We present a novel solution to the Complex-First Paradox. Our solution builds on a generalization of Xu and Tenenbaum’s (XTB07a) Bayesian model of word learning. By focusing on a rational theory of concept learning, we show that it is (...)
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  11.  44
    Keynes’s Coefficient of Dependence Revisited.Peter Brössel - 2015 - Erkenntnis 80 (3):521-553.
    Probabilistic dependence and independence are among the key concepts of Bayesian epistemology. This paper focuses on the study of one specific quantitative notion of probabilistic dependence. More specifically, section 1 introduces Keynes’s coefficient of dependence and shows how it is related to pivotal aspects of scientific reasoning such as confirmation, coherence, the explanatory and unificatory power of theories, and the diversity of evidence. The intimate connection between Keynes’s coefficient of dependence and scientific reasoning raises the question of how Keynes’s coefficient (...)
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  12.  24
    Introduction – Cognitive Penetration and Predictive Coding. Pushing the Debate Forward with the Recent Achievements of Cognitive Science.Albert Newen, Francesco Marchi & Peter Brössel - 2017 - Consciousness and Cognition 47:1-5.
  13.  44
    Theory Assessment and Coherence.Peter Brössel - 2008 - Abstracta 4 (1):57-71.
    One of the most important questions in epistemology and the philosophy of science is: what is a good theory and when is a theory better than another theory, given some observational data? The coherentist‟s answer would be the following twofold conjecture: A theory is a good theory given some observational data iff that theory coheres with the observational data and a theory is better than another theory given some observational data iff the first theory coheres more with the observational data (...)
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    Introduction to the Special Issue “Logical Perspectives on Science and Cognition”.Markus Werning, Peter Brössel, Alexander Gebharter & Christian J. Feldbacher-Escamilla - 2020 - Synthese 197 (4):1381-1390.
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  15.  18
    Correlation and Truth.Peter Brössel - 2013 - In Vassilios Karakostas & Dennis Dieks (eds.), Epsa11 Perspectives and Foundational Problems in Philosophy of Science. Springer. pp. 41--54.
  16.  3
    Rezension: Argumentation in Theorie Und Praxis.Albert Anglberger, Peter Brössel & Melanie Stefan - 2006 - Kriterion - Journal of Philosophy 20 (1):37-41.
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  17. Wahrscheinlichkeit und Erkenntnis.Peter Brössel & Anna-Maria A. Eder - 2013 - In Thomas Bonk (ed.), Lexikon der Erkenntnistheorie.
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