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Profile: Peter Brössel (Ruhr-Universität Bochum)
  1.  46
    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. Evidential Support and Instrumental Rationality.Peter Brössel, Anna-Maria A. Eder & Franz Huber - 2013 - Philosophy and Phenomenological Research 87 (2):279-300.
  3. 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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  4.  40
    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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  5. Bayesian Confirmation: A Means with No End.Peter Brössel & Franz Huber - 2014 - British Journal for the Philosophy of Science (4):axu004.
    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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  6.  33
    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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  7.  12
    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.
  8.  31
    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: (i) A theory is a good theory given some observational data iff that theory coheres with the observational data and (ii) a theory is better than another theory given some observational data iff the first theory coheres more with the (...)
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  9.  45
    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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  10. 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).
  11.  15
    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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  12. 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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  13. Theory Assessment and Coherence.Peter Brössel - 2008 - Abstracta – Linguagem, Mente E Ação 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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