ISBN:
9789400753570
,
1283936097
,
9781283936095
Language:
English
Pages:
Online-Ressource (VIII, 215 p. 23 illus, digital)
Series Statement:
Synthese Library, Studies in Epistemology, Logic, Methodology, and Philosophy of Science 362
Series Statement:
SpringerLink
Series Statement:
Bücher
Parallel Title:
Buchausg. u.d.T. Bayesian argumentation
Keywords:
Philosophy (General)
;
Genetic epistemology
;
Computer simulation
;
Applied linguistics
;
Social sciences Methodology
;
Applied psychology
;
Philosophy
;
Philosophy (General)
;
Genetic epistemology
;
Computer simulation
;
Applied linguistics
;
Social sciences Methodology
;
Applied psychology
;
Reasoning (Psychology)
;
Congresses
;
Logic
;
Congresses
;
Thought and thinking
;
Congresses
;
Probabilities
;
Congresses
;
Bayesian statistical decision theory
;
Congresses
;
Konferenzschrift
;
Argumentationstheorie
;
Bayes-Entscheidungstheorie
Abstract:
Relevant to, and drawing from, a range of disciplines, the chapters in this collection show the diversity, and applicability, of research in Bayesian argumentation. Together, they form a challenge to philosophers versed in both the use and criticism of Bayesian models who have largely overlooked their potential in argumentation. Selected from contributions to a multidisciplinary workshop on the topic held in Lund, Sweden, in autumn 2010, the authors count legal scholars and cognitive scientists among their number, in addition to philosophers. They analyze material that includes real-life court cases, experimental research results, and the insights gained from computer models.The volume provides a formal measure of subjective argument strength and argument force, robust enough to allow advocates of opposing sides of an argument to agree on the relative strengths of their supporting reasoning. With papers from leading figures such as Mike Oaksford and Ulrike Hahn, the book comprises recent research conducted at the frontiers of Bayesian argumentation and provides a multitude of examples in which these formal tools can be applied to informal argument. It signals new and impending developments in philosophy, which has seen Bayesian models deployed in formal epistemology and philosophy of science, but has yet to explore the full potential of Bayesian models as a framework in argumentation. In doing so, this revealing anthology looks destined to become a standard teaching text in years to come.
Description / Table of Contents:
Bayesian Argumentation; Foreword; Contents; Bayesian Argumentation: The Practical Side of Probability; 1 Introduction; 2 The Bayesian Approach to Argumentation; 3 Chapter Overview; 3.1 The Bayesian Approach to Argumentation; 3.2 The Legal Domain; 3.3 Modeling Rational Agents; 3.4 Theoretical Issues; References; Part I: The Bayesian Approach to Argumentation; Testimony and Argument: A Bayesian Perspective; 1 Introduction; 2 Testimony, Argumentation and the `Third Way´; 3 Some Problems for MAXMIN; 4 A Bayesian Perspective; 5 Message Content and Message Source: Exploring Norms and Intuitions
Description / Table of Contents:
6 Rehousing Argumentation Schemes Within a Bayesian Framework7 Concluding Remarks; References; Why Are We Convinced by the Ad Hominem Argument?: Bayesian Source Reliability and Pragma-Dialectical Discussion Rules; 1 Types of the Argumentum Ad Hominem; 2 The Pragma-Dialectical Approach; 3 The Bayesian Approach; 4 An Experiment on the Argument Ad Hominem; 5 Method; 6 Results and Discussion; 7 Conclusion; Appendix: Experimental Materials; Abusive; Circumstantial; Tu Quoque; Control; References; 1 Introduction; 2 Survey of Relevant Uncertainties; Part II: The Legal Domain
Description / Table of Contents:
A Survey of Uncertainties and Their Consequences in Probabilistic Legal Argumentation2.1 The Example Case; 2.2 Factual Uncertainty; 2.3 Normative Uncertainty; 2.4 Moral Uncertainty; 2.5 Empirical Uncertainty; 2.6 Interdependencies; 3 Desirable Attributes for a Probabilistic Argument Model to Assist Litigation Planning; 3.1 Assessment of Utilities; 3.2 Easy Knowledge Engineering; 3.3 Conflict Resolution and Argument Weights; 4 Sample Assessment of Graphical Models; 4.1 A Graphical Structure of the Analysis; 4.2 Casting the Example into a Graphical Model; 4.3 Generic Bayesian Networks
Description / Table of Contents:
5 Carneades5.1 A Brief Introduction to the Carneades Model; 5.2 Carneades Bayesian Networks; 5.3 Carneades Bayesian Networks with Probabilistic Assumptions; 5.4 Introduction to Argument Weights; 6 Extension of Carneades to Support Probabilistic Argument Weights; 7 Desiderata for Future Developments; 7.1 Weights Subject to Argumentation; 7.2 Inform Weights from Values; 8 Conclusions and Future Work; References; Was It Wrong to Use Statistics in R v Clark? A Case Study of the Use of Statistical Evidence in Criminal Courts; 1 Introduction; 2 Factual Background; 3 Existing Explanations
Description / Table of Contents:
3.1 The Flaws in Meadow´s Calculation3.2 The Psychological Effect of the Statistical Evidence; 3.3 The Prosecutor´s Fallacy; 3.4 Bayes´ Theorem; 3.5 The Insignificance of the SIDS Statistics; 4 The Contrastive Explanation; 5 Conclusion; References; Part III: Modeling Rational Agents; A Bayesian Simulation Model of Group Deliberation and Polarization; 1 Introduction; 2 The Laputa Simulation Framework; 3 The Underlying Bayesian Model; 4 Interpreting Laputa; 5 Do Bayesian Inquirers Polarize?; 6 Conclusion and Discussion; Appendix; References
Description / Table of Contents:
Degrees of Justification, Bayes´ Rule, and Rationality
Description / Table of Contents:
Introduction: Frank Zenker.- Part 1 -- The Bayesian Approach to Argumentation -- Chapter 1. Testimony and Argument: A Bayesian Perspective: Ulrike Hahn, Mike Oaksford and Adam J.L. Harris -- Chapter 2. Why are we convinced by the Ad Hominem Argument?: Source Reliability or Pragma-Dialectics: Mike Oaksford and Ulrike Hahn.- Part 2. The Legal Domain.-Chapter 3. A survey of uncertainties and their consequences in Probabilistic Legal Argumentation: Matthias Grabmair and Kevin D. Ashley -- Chapter 4. What went wrong in the case of Sally Clark? A case-study of the use of Statistical Evidence in Court: Amid Pundik -- Part 3. Modeling Rational Agents -- Chapter 5. A Bayesian Simulation Model of Group Deliberation: Erik J. Olsson -- Chapter 6. Degrees of Justification, Bayes' Rule, and Rationality: Gregor Betz -- Chapter 7. Argumentation with (Bounded) Rational Agents: Robert van Rooij and Kris de Jaeghery -- Part 4. Theoretical Issues -- Chapter 8. Reductio, Coherence, and the Myth of Epistemic Circularity: Tomoji Shogenji -- Chapter 9. On Argument Strength: Niki Pfeiffer -- Chapter 10 -- Upping the Stakes and the Preface Paradox: Jonny Blamey -- References..
Note:
Description based upon print version of record
DOI:
10.1007/978-94-007-5357-0
URL:
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