Peter Brössel
Biographic Data
| ID | 1100889 |
|---|---|
| NAME | Peter Brössel |
| GIVEN NAMES | Peter |
| FAMILY NAME | Brössel |
| SIGNATURE | BRÖSSEL P |
| AFFILIATIONS | Ruhr University Bochum |
| ORCID | 0000-0003-1992-6826 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 29 |
| WORKS AS AUTHOR | 8 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2012 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 3 |
Learning from experience and conditionalization
Bayesianism can be characterized as the following twofold position: (i) rational credences obey the probability calculus; (ii) rational learning, i.e., the updating of credences, is regulated by some form of conditionalization. While the formal aspect of various forms of conditionalization has been explored in detail, the philosophical application to learning from experience is still deeply problematic. Some philosophers have proposed to revise t…
Introduction to the special issue “Logical perspectives on science and cognition”
Learning Concepts
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 (Markus Werning). This is the complex-first paradox. We present a novel solution to the complex-first paradox. Our solution builds on a generalization of Fei Xu and Joshua B. Tenenbaum’s Bayesian model of word learning…
On the role of explanatory and systematic power in scientific reasoning
Bayesian Confirmation
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 epist…
How to resolve doxastic disagreement
The Problem of Measure Sensitivity Redux
Fitelson demonstrates that the validity of various central arguments within Bayesian confirmation theory depends on which confirmation measure is adopted. This article adds to the results set out by Fitelson, 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 …
Evidential Support and Instrumental Rationality
The Problem of Measure Sensitivity Redux
Fitelson demonstrates that the validity of various central arguments within Bayesian confirmation theory depends on which confirmation measure is adopted. This article adds to the results set out by Fitelson, 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 …
How to resolve doxastic disagreement
Evidential Support and Instrumental Rationality
Bayesian Confirmation
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 epist…
Learning Concepts
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 (Markus Werning). This is the complex-first paradox. We present a novel solution to the complex-first paradox. Our solution builds on a generalization of Fei Xu and Joshua B. Tenenbaum’s Bayesian model of word learning…
On the role of explanatory and systematic power in scientific reasoning
Evidential Support and Instrumental Rationality
The Problem of Measure Sensitivity Redux
Fitelson demonstrates that the validity of various central arguments within Bayesian confirmation theory depends on which confirmation measure is adopted. This article adds to the results set out by Fitelson, 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 …
How to resolve doxastic disagreement
On the role of explanatory and systematic power in scientific reasoning
Bayesian Confirmation
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 epist…
Introduction to the special issue “Logical perspectives on science and cognition”
Learning Concepts
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 (Markus Werning). This is the complex-first paradox. We present a novel solution to the complex-first paradox. Our solution builds on a generalization of Fei Xu and Joshua B. Tenenbaum’s Bayesian model of word learning…
Learning from experience and conditionalization
Bayesianism can be characterized as the following twofold position: (i) rational credences obey the probability calculus; (ii) rational learning, i.e., the updating of credences, is regulated by some form of conditionalization. While the formal aspect of various forms of conditionalization has been explored in detail, the philosophical application to learning from experience is still deeply problematic. Some philosophers have proposed to revise t…
Epistemology (8 works) · Philosophy (8 works) · Artificial Intelligence (6 works) · Computer Science (6 works) · Artificial Intelligence (5 works) · Philosophy and History of Science (5 works) · Psychology (5 works) · Bayesian probability (4 works) · Epistemology, Ethics, and Metaphysics (4 works) · Metaphysics (4 works)