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Reflections on the Foundations of Probability and Statistics

Essays in Honor of Teddy Seidenfeld
BuchGebunden
346 Seiten
Englisch
Springererschienen am15.01.20231st ed. 2022
The reader is invited to share this celebration of Teddy Seidenfeld´s work uncovering truths about uncertainty and the penetrating insights they offer to our common pursuit of truth in the face of uncertainty.mehr
Verfügbare Formate
BuchGebunden
EUR128,39
BuchKartoniert, Paperback
EUR128,39
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Produkt

KlappentextThe reader is invited to share this celebration of Teddy Seidenfeld´s work uncovering truths about uncertainty and the penetrating insights they offer to our common pursuit of truth in the face of uncertainty.
Zusammenfassung
Brings together quality scholarship

Examines findings in imprecise probability

Contains unique state-of-the-art research
Details
ISBN/GTIN978-3-031-15435-5
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2023
Erscheinungsdatum15.01.2023
Auflage1st ed. 2022
ReiheTheory and Decision Library A:
Seiten346 Seiten
SpracheEnglisch
IllustrationenXII, 346 p. 33 illus., 21 illus. in color.
Artikel-Nr.16576287

Inhalt/Kritik

Inhaltsverzeichnis
An Interview with Teddy Seidenfeld.- The Value Provided by a Scientific Explanation.- A Gentle Approach to Imprecise Probability.- Foundations For Temporal Reasoning Using Lower Previsions Without A Possibility Space.- On the Equivalence of Normal and Extensive Form Representations of Games.- Dilation and Informativeness.- Playing with Sets of Lexicographic Probabilities and Sets of Desirable Gambles.- How to Assess Coherent Beliefs: A Comparison of Different Notions of Coherence in Dempster-Shafer Theory of Evidence.- Expected Utility in 3D.- On the Normative Status of Mixed Strategies.- On a Notion of Independence Proposed by Teddy Seidenfeld.- Coherent Choice Functions without Archimedeanity.- Quantifying Degrees of E-admissibility in Decision Making with Imprecise Probabilities.mehr

Schlagworte

Autor

Thomas Augustin is Professor of Statistics at Ludwig-Maximilians-Universität München (LMU Munich), where he heads the "Foundations of Statistics and their Applications" Lab. His research interest is to develop set-valued methods for reliable statistical inference, decision making, and machine learning. For this, he utilizes
concepts from imprecise probabilities and partial identification to cope with different kinds of complex uncertainty, like non-randomly missing or coarsened data, non-standard measurement error, ambiguity,
conflicting information, and structural model indeterminacy.

Fabio G. Cozman is Professor of Computer Science at Escola Politécnica, Universidade de São Paulo (USP), Director of the Center for Artificial Intelligence at USP, with an interest in machine learning and knowledge/uncertainty representation. Engineer (USP) and PhD (Carnegie Mellon University, USA), he has served as Program and General Chair of the Conference on Uncertainty in Artificial Intelligence, Area Chair of the International Joint Conference on Artificial Intelligence, and Associate Editor of the Artificial Intelligence Journal, the Journal of Artificial Intelligence Research, and the Journal of Approximate Reasoning.

Gregory Wheeler is Professor of Philosophy and Computer Science at Frankfurt School of Finance & Management, where he heads the Center for Human & Machine Intelligence and is Academic Director of the Master of Applied Data Science program. His research interests concern the foundations of probability, bounded rationality, and decision-making under uncertainty involving underspecified models, conflicting information, computational resource bounds, and indeterminacy. He also co-founded Exaloan AG, a Frankfurt-based financial services software company, where he is Head of Machine Learning.
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