Preface |
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ix | |
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1 The Problem of Induction |
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1 | (10) |
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1.1 The Notion of Induction: Conceptual Clarifications |
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1 | (4) |
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1.2 David Hume and the Problem of Justifying Induction |
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5 | (3) |
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8 | (3) |
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2 On Failed Attempts to Solve the Problem of Induction |
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11 | (16) |
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2.1 Can Induction Be Avoided? |
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11 | (2) |
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2.2 Is Induction Rational "by Definition"? Rationality and Cognitive Success |
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13 | (3) |
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2.3 Can Induction Be Justified by Assumptions of Uniformity? |
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16 | (2) |
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2.4 Can Circular Justifications of Induction Have Epistemic Value? |
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18 | (4) |
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2.5 Can Induction Be Justified by Abduction or Inference to the Best Explanation? |
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22 | (2) |
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2.6 The Role of Induction and Abduction for Instrumentalism and Realism |
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24 | (3) |
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3 The Significance of Hume's Problem for Contemporary Epistemology |
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27 | (20) |
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3.1 The Aims of Epistemology |
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27 | (2) |
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3.2 Foundation-Oriented Epistemology and Its Main Problems |
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29 | (6) |
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3.3 Coherentism and Its Shortcomings |
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35 | (3) |
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3.4 Externalism and Its Shortcomings |
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38 | (5) |
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3.5 The Necessity of Reliability Indicators for the Social Spread of Knowledge |
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43 | (1) |
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3.6 Conclusion: A Plea for Foundation-Oriented Epistemology |
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44 | (3) |
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4 Are Probabilistic Justifications of Induction Possible? |
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47 | (30) |
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4.1 Why Genuine Confirmation Needs Induction Axioms |
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47 | (5) |
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4.2 Digression: Goodman's Paradox and the Problem of Language Relativity |
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52 | (5) |
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4.3 Statistical Principal Principle and Narrowest Reference Classes |
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57 | (4) |
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4.4 Statistical Principal Principle and Exchangeability as Weak Induction Axioms |
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61 | (7) |
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4.5 Indifference Principle as an Induction Axiom |
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68 | (4) |
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4.6 Inductive Probabilities without the Principle of Indifference? |
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72 | (3) |
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4.7 Is Skepticism Unavoidable? |
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75 | (2) |
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5 A New Start: Meta-Induction, Optimality Justifications, and Prediction Games |
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77 | (32) |
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5.1 Reichenbach's Best Alternative Approach |
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77 | (1) |
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5.2 Reliability Justifications versus Optimality Justifications |
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78 | (3) |
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5.3 Shortcomings of Reichenbach's Best Alternative Approach |
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81 | (1) |
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5.4 Object-Induction versus Meta-Induction |
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82 | (3) |
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85 | (5) |
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5.6 Classification of Prediction Methods and Game-Theoretic Reflections |
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90 | (4) |
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5.7 Definitions of Optimality, Access-Optimality, and (Access-) Dominance |
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94 | (5) |
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5.8 Three Related Approaches: Formal Learning Theory, Computational Learning Theory, and Ecological Rationality Research |
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99 | (3) |
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5.9 Simple and Refined (Conditionalized) Inductive Methods |
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102 | (7) |
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6 Kinds of Meta-Inductive Strategies and Their Performance |
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109 | (54) |
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6.1 Imitate the Best (ITB): Achievements and Failures |
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110 | (12) |
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6.2 Epsilon-Cautious Imitate the Best (εITB) |
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122 | (4) |
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6.3 Systematic Deception: Fundamental Limitations of One-Favorite Meta-lnduction |
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126 | (5) |
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6.3.1 General Facts about Nonconverging Frequencies |
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126 | (1) |
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6.3.2 Nonconvergent Success Oscillations and Systematic Deceivers |
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127 | (2) |
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6.3.3 Limitations of One-Favorite Meta-Induction |
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129 | (2) |
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6.4 Deception Detection and Avoidance Meta-Induction (ITBN) |
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131 | (4) |
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6.5 Further Variations of One-Favorite Meta-Induction |
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135 | (3) |
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6.6 Attractivity-Weighted Meta-Induction (AW) for Real-Valued Predictions |
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138 | (9) |
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140 | (4) |
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144 | (1) |
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6.6.3 Access-Superoptimality |
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145 | (2) |
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6.7 Attractivity-Weighted Meta-Induction for Discrete Predictions |
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147 | (9) |
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6.7.1 Randomized AW Meta-Induction |
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149 | (4) |
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6.7.2 Collective AW Meta-Induction |
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153 | (3) |
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6.8 Further Variants of Weighted Meta-Induction |
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156 | (7) |
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6.8.1 Success-Based Weighting |
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157 | (4) |
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6.8.2 Worst-Case Regrets and Division of Epistemic Labor |
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161 | (2) |
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7 Generalizations and Extensions |
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163 | (34) |
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7.1 Bayesian Predictors and Meta-Inductive Probability Aggregation |
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163 | (6) |
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7.2 Intermittent Prediction Games |
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169 | (11) |
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7.2.1 Take the Best (TTB) |
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172 | (5) |
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177 | (3) |
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7.3 Unboundedly Growing Numbers of Players |
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180 | (6) |
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7.3.1 New Players with Self-Completed Success Evaluation |
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181 | (2) |
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7.3.2 Meta-Induction over Player Sequences |
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183 | (3) |
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7.4 Prediction of Test Sets |
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186 | (2) |
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7.5 Generalization to Action Games |
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188 | (3) |
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7.6 Adding Cognitive Costs |
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191 | (3) |
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7.7 Meta-Induction in Games with Restricted Information |
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194 | (3) |
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8 Philosophical Conclusions and Refinements |
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197 | (36) |
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8.1 A Noncircular Solution to Hume's Problem |
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197 | (18) |
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8.1.1 Epistemological Explication of the Optimality Argument |
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197 | (6) |
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8.1.2 Radical Openness and Universal Learning Ability |
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203 | (1) |
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8.1.3 Meta-Induction and Fundamental Disagreement |
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204 | (2) |
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8.1.4 Fundamentalistic Strategies and the Freedom to Learn |
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206 | (2) |
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8.1.5 A Posteriori Justification of Object-Induction |
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208 | (2) |
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8.1.6 Bayesian Interpretation of the Optimality Argument |
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210 | (2) |
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8.1.7 From Optimal Predictions to Rational (Degrees of) Belief |
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212 | (3) |
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8.2 Conditionalized Meta-Induction |
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215 | (7) |
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8.3 From Optimality to Dominance |
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222 | (11) |
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8.3.1 Restricted Dominance Results |
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222 | (2) |
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8.3.2 Discriminating between Inductive and Noninductive Prediction Methods |
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224 | (4) |
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8.3.3 Bayesian Interpretation of Dominance |
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228 | (5) |
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9 Defense against Objections |
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233 | (40) |
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9.1 Meta-Induction and the No Free Lunch Theorem |
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233 | (27) |
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9.1.1 The Long-Run Perspective |
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235 | (10) |
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9.1.2 The Short-Run Perspective |
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245 | (15) |
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9.2 The Problem of Infinitely Many Prediction Methods |
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260 | (13) |
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9.2.1 Infinitely Many Methods and Failure of Access-Optimality |
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260 | (2) |
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9.2.2 Restricted Optimality Results for Infinitely Many Methods |
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262 | (4) |
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9.2.3 Defense of the Cognitive Finiteness Assumption |
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266 | (2) |
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9.2.4 The Problem of Selecting the Candidate Set |
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268 | (2) |
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9.2.5 Goodman's Problem at the Level of Prediction Methods |
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270 | (3) |
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10 Interdisciplinary Applications |
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273 | (32) |
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10.1 Meta-Induction and Ecological Rationality: Application to Cognitive Science |
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273 | (11) |
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10.2 Meta-Induction and Spread of Knowledge: Application to Social Epistemology |
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284 | (13) |
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10.2.1 Prediction Games in Epistemic Networks |
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287 | (2) |
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10.2.2 Local Meta-Induction and Spread of Reliable Information |
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289 | (4) |
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10.2.3 Imitation without Success Information: Consensus Formation without Spread of Knowledge |
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293 | (2) |
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295 | (2) |
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10.3 Meta-Induction, Cooperation, and Game Theory: Application to Cultural Evolution |
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297 | (8) |
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11 Conclusion and Outlook: Optimality Justifications as a Philosophical Program |
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305 | (10) |
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11.1 Optimality Justifications as a Means of Stopping the Justificational Regress |
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305 | (2) |
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11.2 Generalizing Optimality Justifications |
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307 | (7) |
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11.2.1 The Problem of the Basis: Introspective Beliefs |
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307 | (1) |
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11.2.2 The Choice of the Logic |
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307 | (3) |
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11.2.3 The Choice of a Conceptual System |
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310 | (1) |
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11.2.4 The Choice of a Theory |
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310 | (1) |
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11.2.5 The Justification of Abductive Inference |
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311 | (3) |
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11.3 New Foundations for Foundation-Oriented Epistemology |
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314 | (1) |
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12 Appendix: Proof of Formal Results |
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315 | (32) |
Formal Symbols and Abbreviations |
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347 | (4) |
Memos, Definitions, Propositions, Theorems, Figures, and Tables |
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351 | (4) |
References |
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355 | (16) |
Subject Index |
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371 | (12) |
Author Index |
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383 | |