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Philosophy of Probability Wenmackers, S University of Groningen Philosophy of probability Wenmackers, S. IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2011 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Wenmackers, S. (2011). Philosophy of probability: Foundations, epistemology, and computation. s.n. Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). The publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license. More information can be found on the University of Groningen website: https://www.rug.nl/library/open-access/self-archiving-pure/taverne- amendment. Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum. Download date: 01-10-2021 Philosophy of Probability Foundations, Epistemology, and Computation Sylvia Wenmackers The work described in this thesis was carried out in the Formal Epistemology Project (FEP) of the Theoretical Philosophy (TP) group, which belongs to the Faculty of Philosophy of the University of Groningen. PhD-dissertation of University of Groningen Title: Philosophy of Probability Author: S. Wenmackers ISBN: 978-90-367-4870-4 (ISBN printed version: 978-90-367-4869-8) Publisher: University of Groningen, The Netherlands Printed by: Reproduct, Ghent, Belgium © S. Wenmackers, 2011 Cover: `Zero probability reveals its infinite depths.' The cover image shows `P = 0', in a composition made of dice|a material representation of the abstract concept of chance. The rippled edge of the right-hand picture refers to hydromancy: a method of divination by means of water. In modern times, we still feel a need for predicting the future, but we rely on science to inform of us of the relevant probabilities. This method is riddled with mysteries of its own: the interpretation of events with zero probability is notoriously complicated. To resolve these difficulties, we need a con- cept of probability that is more fine-grained than the real numbers. RIJKSUNIVERSITEIT GRONINGEN Philosophy of Probability Foundations, Epistemology, and Computation Proefschrift ter verkrijging van het doctoraat in de Wijsbegeerte aan de Rijksuniversiteit Groningen op gezag van de Rector Magnificus, dr. E. Sterken, in het openbaar te verdedigen op maandag 2 mei 2011 om 16.15 uur door Sylvia Wenmackers geboren op 12 mei 1980 te Maasmechelen, Belgi¨e Promotor: Prof. dr. mr. I. E. J. Douven Beoordelingscommissie: Prof. dr. L. Horsten Prof. dr. J. Peijnenburg Prof. dr. T. Williamson He deals the cards to find the answer The sacred geometry of chance The hidden law of a probable outcome The numbers lead a dance \Shape Of My Heart"|Sting vii Contents 1 Introduction1 1.1 Motivation and structure . .1 1.2 From formal to computational philosophy . .4 1.2.1 Formal philosophy . .4 1.2.2 Computational philosophy . .6 1.2.3 Chances for philosophy . .7 1.2.4 Use with caution . .8 1.3 Foundations of probability and randomness . .9 1.3.1 Interpretations of probability . .9 1.3.2 An epistemic approach to objective probability . 11 1.3.3 Definition of a chance process . 14 1.3.3.1 Possible outcomes: from possible worlds to multiverse 15 1.3.3.2 Odds: fair, weighted, or unknown . 17 1.3.4 Measuring randomness . 18 1.3.4.1 Looking for patterns . 18 1.3.4.2 Mathematical approach to randomness . 20 1.3.5 Producing (pseudo-)random numbers . 21 1.3.5.1 Pseudo-random numbers . 21 1.3.5.2 True random numbers . 22 1.3.5.3 Making up random numbers . 23 1.3.6 Amount of certainty . 24 1.3.7 Relation of probability to luck and justice . 25 1.4 Infinity and probability . 27 1.4.1 Measuring infinite sets . 27 1.4.1.1 Historic dispute . 28 1.4.1.2 Cantor's cardinal numbers . 29 1.4.1.3 Numerosities . 30 1.4.1.4 Cardinality versus numerosity . 31 1.4.2 Infinite sample spaces . 31 1.4.2.1 Kolmogorov's axioms . 32 1.4.2.2 Various approaches and their problems . 33 1.4.2.3 Countably infinite sample spaces . 34 viii CONTENTS 1.4.2.4 Infinite sample spaces and additivity of probability . 36 1.4.3 Implications for cases with finite sample spaces . 36 2 Fair Infinite Lotteries 39 2.1 Introduction: from the finite to the transfinite . 39 2.2 Intuitions concerning lotteries . 41 2.2.1 Finite lotteries . 41 2.2.1.1 Probability measure . 41 2.2.1.2 Intuitions . 42 2.2.2 Infinite lotteries . 43 2.3 Asymptotic density: real-valued probability with finite additivity . 44 2.3.1 Limiting relative frequency . 44 2.3.2 A generalization . 44 2.4 Infinitesimals . 45 2.4.1 The star-map and Transfer . 45 2.4.2 Equivalence classes based on a free ultrafilter . 46 2.4.3 N and Q ............................... 47 2.4.4 R∗ as an∗ approximation to Q .................... 47 2.4.5 Limits . .∗ . 48 2.4.5.1 Alpha-limit . 48 2.4.5.2 Classical limit . 48 2.4.5.3 Hahn-Banach limit . 48 2.4.6 Internal and external objects . 48 2.5 Hyperrational valued probability . 49 2.5.1 The construction . 49 2.5.1.1 Step 1: Characteristic bit string . 49 2.5.1.2 Step 2: Partial sums of characteristic bit strings . 49 2.5.1.3 Step 3: Numerosity . 50 2.5.1.4 Step 4: Non-standard probability . 51 2.5.2 Additivity of the probability function . 51 2.5.2.1 Addition on N ....................... 52 2.5.2.2 num is not CA∗ . 52 2.5.2.3 num of a sequence of sets . 52 2.5.2.4 num and Pnum are HCA . 53 2.6 Discussion . 56 2.6.1 Non-constructiveness . 56 2.6.2 Non-uniqueness . 56 2.6.3 Lotteries on N versus hyperfinite lotteries . 57 2.6.4 Non-standard probability and asymptotic density . 58 2.6.4.1 Co-domain R versus Q .................. 58 2.6.4.2 Standard valued approximations∗ and the failure of SUM 59 2.7 Conclusion . 61 CONTENTS ix 3 Stratified Belief and Ultralarge Lotteries 63 3.1 Introduction . 63 3.2 Mapping [0; 1] onto {0; 1} .......................... 66 3.3 Threshold-based model of the Lottery Paradox . 68 3.3.1 Formalizing the Lockean Thesis . 68 3.3.2 Illustration of the failure of CP . 69 3.4 The vague lottery: a heap of tickets . 69 3.4.1 Observation 1: The soritic lottery . 70 3.4.2 Observation 2: Contextual element . 70 3.4.3 Observation 3: Analogy with fair lottery on N .......... 70 3.4.4 Observation 4: Weakening CP . 72 3.5 Introduction to relative analysis . 73 3.5.1 Vagueness in physics . 73 3.5.2 Scales of magnitude . 75 3.5.3 Levels . 75 3.5.3.1 Axioms for levels . 76 3.5.3.2 Further terminology . 77 3.5.4 What levels are: a predicate on the domain . 78 3.5.5 What levels are not: sets . 78 3.5.6 The grain of sand, the bucket, and the beach . 79 3.6 Analysis of the Lottery Paradox using relative analysis . 80 3.6.1 Stratified model for rational belief . 80 3.6.2 Stratified belief applied to a large lottery . 81 3.6.3 Aggregation of stratified beliefs . 83 3.6.3.1 Aggregating beliefs concerning single lottery tickets . 83 3.6.3.2 Generalization of SCP . 83 3.6.4 Is the solution psychologically plausible? . 84 3.7 Relation to philosophical theories and application to other problems . 85 3.7.1 Relation to contextualism . 85 3.7.2 Relation to the epistemicist account of vagueness . 87 3.7.2.1 Threshold-free scales of belief . 87 3.7.2.2 Vague thresholds . 87 3.7.3 Application of Stratified Belief to similar problems . 88 3.8 Conclusions . 89 4 Ultralarge and Infinite Lotteries 91 4.1 Introduction . 91 4.1.1 Case 1: Failure of Countable Additivity (infinite lottery) . 92 4.1.2 Case 2: Failure of Conjunction Principle (ultralarge lottery) . 93 4.2 The analogy between the two cases . 93 4.3 Solution using non-standard analysis . 95 4.3.1 Infinite additivity for a fair lottery on N ............. 95 4.3.2 Conjunction Principle within a level . 96 4.3.3 Visual summary of the solution . 97 4.4 The epistemology of an infinite lottery . 97 x CONTENTS 5 Probability of Inconsistencies 99 5.1 Introduction . 99 5.1.1 Content of an agent's opinion . 101 5.1.2 Update rule for opinions . 102 5.1.3 Opinion profile . 103 5.1.4 Time . 103 5.1.5 Group size . 103 5.1.6 Research question . 104 5.2 Preliminaries . 104 5.2.1 Logical framework . 104 5.2.1.1 Language and consequence relation . 104 5.2.1.2 Possible worlds . 105 5.2.1.3 Theories . 106 5.2.2 Opinion profile .
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