| List of Abbreviations |
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xxxvii | |
| Part A Theoretical Issues in Models |
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5 | (20) |
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1.1 Kinds of Models: Examples from Scientific Practice |
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6 | (2) |
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1.2 The Nature and Function of Models |
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8 | (2) |
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1.3 Models as Analogies and Metaphors |
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10 | (2) |
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1.4 Models Versus the Received View: Sentences and Structures |
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12 | (4) |
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1.5 The Folk Ontology of Models |
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16 | (2) |
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18 | (2) |
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1.7 Mixed Ontologies: Models as Mediators and Epistemic Artifacts |
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20 | (1) |
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21 | (1) |
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22 | (3) |
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25 | (24) |
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2.1 The Received View of Scientific Theories |
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26 | (10) |
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2.2 The Semantic View of Scientific Theories |
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36 | (11) |
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47 | (2) |
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3 Models and Representation |
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49 | (54) |
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3.1 Problems Concerning Model-Representation |
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51 | (4) |
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3.2 General Griceanism and Stipulative Fiat |
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55 | (2) |
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3.3 The Similarity Conception |
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57 | (9) |
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3.4 The Structuralist Conception |
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66 | (10) |
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3.5 The Inferential Conception |
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76 | (7) |
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3.6 The Fiction View of Models |
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83 | (8) |
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91 | (5) |
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96 | (1) |
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96 | (7) |
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103 | (16) |
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4.1 The Explanatory Function of Models |
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104 | (4) |
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4.2 Explanatory Fictions: Can Falsehoods Explain? |
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108 | (4) |
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4.3 Explanatory Models and Noncausal Explanations |
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112 | (2) |
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4.4 How-Possibly versus How-Actually Model Explanations |
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114 | (1) |
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4.5 Tradeoffs in Modeling: Explanation versus Other Functions for Models |
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115 | (1) |
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116 | (1) |
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117 | (2) |
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119 | (18) |
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5.1 Theory-Based Simulation |
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119 | (2) |
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5.2 Simulation not Driven by Theory |
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121 | (3) |
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5.3 What is Philosophically Novel About Simulation? |
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124 | (3) |
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5.4 Computational Simulation and Human Cognition |
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127 | (3) |
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130 | (7) |
| Part B Theoretical and Cognitive Issues on Abduction and Scientific Inference |
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6 Reorienting the Logic of Abduction |
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137 | (14) |
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138 | (3) |
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141 | (7) |
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148 | (1) |
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149 | (2) |
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7 Patterns of Abductive Inference |
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151 | (24) |
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7.1 General Characterization of Abductive Reasoning and Ibe |
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152 | (2) |
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7.2 Three Dimensions for Classifying Patterns of Abduction |
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154 | (1) |
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155 | (3) |
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158 | (1) |
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7.5 Theoretical-Model Abduction |
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159 | (2) |
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7.6 Second-Order Existential Abduction |
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161 | (1) |
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7.7 Hypothetical (Common) Cause Abduction Continued |
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162 | (7) |
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7.8 Further Applications of Abductive Inference |
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169 | (2) |
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171 | (4) |
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8 Forms of Abduction and an Inferential Taxonomy |
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175 | (22) |
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8.1 Abduction in the Overall Inferential Context |
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177 | (6) |
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8.2 The Logicality of Abduction, Deduction, and Induction |
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183 | (2) |
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185 | (4) |
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8.4 Discussion of Two Important Distinctions Between Types of Abduction |
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189 | (4) |
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193 | (1) |
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193 | (4) |
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9 Magnani's Manipulative Abduction |
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197 | (22) |
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9.1 Magnani's Distinction Between Theoretical and Manipulative Abduction |
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197 | (1) |
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9.2 Manipulative Abduction in Diagrammatic Reasoning |
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198 | (5) |
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9.3 When Does Manipulative Abduction Take Place? |
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203 | (1) |
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9.4 Manipulative Abduction as a Form of Practical Reasoning |
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204 | (2) |
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9.5 The Ubiquity of Manipulative Abduction |
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206 | (6) |
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212 | (1) |
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212 | (7) |
| Part C The Logic of Hypothetical Reasoning, Abduction, and Models |
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10 The Logic of Abduction: An Introduction |
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219 | (12) |
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219 | (3) |
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222 | (3) |
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10.3 Three Characterizations |
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225 | (3) |
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228 | (1) |
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229 | (2) |
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11 Qualitative Inductive Generalization and Confirmation |
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231 | (18) |
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11.1 Adaptive Logics for Inductive Generalization |
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231 | (1) |
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11.2 A First Logic for Inductive Generalization |
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232 | (5) |
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11.3 More Adaptive Logics for Inductive Generalization |
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237 | (3) |
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11.4 Qualitative Inductive Generalization and Confirmation |
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240 | (5) |
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245 | (1) |
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11.A Appendix: Blocking the Raven Paradox? |
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246 | (1) |
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247 | (2) |
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12 Modeling Hypothetical Reasoning by Formal Logics |
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249 | (20) |
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12.1 The Feasibility of the Project |
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249 | (2) |
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12.2 Advantages and Drawbacks |
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251 | (1) |
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12.3 Four Patterns of Hypothetical Reasoning |
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252 | (3) |
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12.4 Abductive Reasoning and Adaptive Logics |
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255 | (1) |
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12.5 The Problem of Multiple Explanatory Hypotheses |
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256 | (1) |
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12.6 The Standard Format of Adaptive Logics |
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256 | (2) |
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12.7 LArs: A Logic for Practical Singular Fact Abduction |
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258 | (3) |
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12.8 MLAss: A Logic for Theoretical Singular Fact Abduction |
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261 | (4) |
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265 | (1) |
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12.A Appendix: Formal Presentations of the Logics LArs and MLAss |
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265 | (2) |
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267 | (2) |
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13 Abductive Reasoning in Dynamic Epistemic Logic |
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269 | (26) |
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Angel Nepomuceno-Fernandez |
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Fernando R. Velazquez-Quesada |
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270 | (2) |
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13.2 A Dynamic Epistemic Perspective |
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272 | (3) |
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13.3 Representing Knowledge and Beliefs |
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275 | (3) |
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13.4 Abductive Problem and Solution |
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278 | (3) |
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13.5 Selecting the Best Explanation |
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281 | (3) |
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13.6 Integrating the Best Solution |
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284 | (3) |
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13.7 Working with the Explanations |
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287 | (2) |
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13.8 A Brief Exploration to Nonideal Agents |
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289 | (1) |
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290 | (2) |
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292 | (3) |
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14 Argumentation and Abduction in Dialogical Logic |
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295 | (20) |
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14.1 Reasoning as a Human Activity |
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295 | (2) |
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14.2 Logic and Argumentation: The Divorce |
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297 | (2) |
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14.3 Logic and Argumentation: A Reconciliation |
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299 | (4) |
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14.4 Beyond Deductive Inference: Abduction |
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303 | (3) |
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14.5 Abduction in Dialogical Logic |
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306 | (4) |
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14.6 Hypothesis: What Kind of Speech Act? |
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310 | (2) |
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312 | (1) |
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312 | (3) |
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15 Formal (In)consistency, Abduction and Modalities |
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315 | (26) |
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315 | (1) |
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15.2 Logics of Formal Inconsistency |
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316 | (6) |
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322 | (5) |
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327 | (4) |
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15.5 On Alternative Semantics for mbC |
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331 | (2) |
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333 | (1) |
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334 | (7) |
| Part D Model-Based Reasoning in Science and the History of Science |
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16 Metaphor and Model-Based Reasoning in Mathematical Physics |
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341 | (14) |
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16.1 Cognitive Tools for Interpretive Understanding |
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343 | (2) |
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16.2 Maxwell's Use of Mathematical Representation |
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345 | (3) |
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16.3 Unpacking the Model-Based Reasoning |
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348 | (2) |
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16.4 Cognition and Metaphor in Mathematical Physics |
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350 | (1) |
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351 | (1) |
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352 | (3) |
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17 Nancy Nersessian's Cognitive-Historical Approach |
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355 | (22) |
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Nora Alejandrina Schwartz |
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17.1 Questions About the Creation of Scientific Concepts |
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356 | (3) |
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17.2 The Epistemic Virtues of Cognitive Historical Analysis |
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359 | (4) |
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17.3 Hypothesis About the Creation of Scientific Concepts |
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363 | (10) |
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373 | (1) |
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373 | (4) |
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18 Physically Similar Systems - A History of the Concept |
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377 | (36) |
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18.1 Similar Systems, the Twentieth Century Concept |
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379 | (1) |
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380 | (3) |
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18.3 Late Nineteenth and Early Twentieth Century |
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383 | (14) |
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18.4 1914: The Year of Physically Similar Systems |
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397 | (11) |
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18.5 Physically Similar Systems: The Path in Retrospect |
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408 | (1) |
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409 | (4) |
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19 Hypothetical Models in Social Science |
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413 | (22) |
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19.1 Hypothetical Modeling as a Style of Reasoning |
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413 | (3) |
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19.2 Models Versus Experiments: Representation, Isolation and Resemblance |
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416 | (4) |
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19.3 Models and Simulations: Complexity, Tractability and Transparency |
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420 | (3) |
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19.4 Epistemology of Models |
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423 | (5) |
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428 | (1) |
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19.A Appendix: J.H. von Thunen's Model of Agricultural Land Use in the Isolated State |
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429 | (1) |
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19.B Appendix: T. Schelling's Agent-Based Model of Segregation in Metropolitan Areas |
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430 | (1) |
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431 | (4) |
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435 | (28) |
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20.1 A Basic Model for Diagnosis |
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437 | (1) |
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20.2 A Review and Taxonomy of Knowledge Engineering Methods for Diagnosis |
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438 | (2) |
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20.3 Model-Based Diagnostic Reasoning |
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440 | (1) |
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20.4 A Motivation Example |
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440 | (2) |
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20.5 Theory of Model-Based Diagnosis |
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442 | (2) |
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444 | (2) |
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20.7 Potential Conflict Structures |
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446 | (2) |
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20.8 Example Revisited. A Complete Diagnostic Procedure |
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448 | (2) |
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20.9 Refinement: Qualitative Diagnoses |
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450 | (4) |
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20.10 Dynamic Systems Diagnosis: The Three-Tank Case |
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454 | (2) |
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20.11 Incremental Diagnosis |
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456 | (2) |
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20.12 Practical Example and Tools |
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458 | (1) |
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459 | (1) |
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460 | (3) |
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21 Thought Experiments in Model-Based Reasoning |
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463 | (36) |
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464 | (3) |
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21.2 Historical Background |
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467 | (2) |
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21.3 What Is a Thought Experiment? |
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469 | (6) |
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21.4 What Is the Function of Thought Experiments? |
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475 | (9) |
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21.5 How Do Thought Experiments Achieve Their Function? |
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484 | (3) |
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487 | (12) |
| Part E Models in Mathematics |
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22 Diagrammatic Reasoning in Mathematics |
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499 | (24) |
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22.1 Diagrams as Cognitive Tools |
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499 | (2) |
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22.2 Diagrams and (the Philosophy of) Mathematical Practice |
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501 | (2) |
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22.3 The Euclidean Diagram |
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503 | (6) |
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22.4 The Productive Ambiguity of Diagrams |
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509 | (1) |
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22.5 Diagrams in Contemporary Mathematics |
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510 | (5) |
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22.6 Computational Approaches |
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515 | (3) |
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22.7 Mathematical Thinking: Beyond Binary Classifications |
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518 | (2) |
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520 | (1) |
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521 | (2) |
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23 Deduction, Diagrams and Model-Based Reasoning |
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523 | (14) |
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23.1 Euclid's Systematic Use of Geometric Diagrams |
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524 | (1) |
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23.2 Formalizing Euclid's Diagrammatic Proof Method |
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525 | (7) |
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23.3 Formal Geometric Diagrams as Models |
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532 | (2) |
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534 | (3) |
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24 Model-Based Reasoning in Mathematical Practice |
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537 | (14) |
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537 | (1) |
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24.2 Model-Based Reasoning: Examples |
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538 | (2) |
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24.3 The Power of Heuristics and Plausible Reasoning |
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540 | (2) |
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24.4 Mathematical Fruits of Model-Based Reasoning |
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542 | (4) |
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546 | (1) |
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546 | (2) |
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548 | (3) |
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25 Abduction and the Emergence of Necessary Mathematical Knowledge |
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551 | (22) |
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25.1 An Example from the Classroom |
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551 | (4) |
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555 | (6) |
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25.3 Abduction in Math and Science Education |
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561 | (3) |
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25.4 Enacting Abductive Action in Mathematical Contexts |
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564 | (2) |
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566 | (7) |
| Part F Model-Based Reasoning in Cognitive Science |
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26 Vision, Thinking, and Model-Based Inferences |
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573 | (32) |
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26.1 Inference and Its Modes |
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576 | (1) |
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577 | (8) |
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26.3 Stages of Visual Processing |
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585 | (3) |
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26.4 Cognitive Penetrability of Perception and the Relation Between Early Vision and Thinking |
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588 | (3) |
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26.5 Late Vision, Inferences, and Thinking |
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591 | (5) |
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26.6 Concluding Discussion |
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596 | (1) |
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26.A Appendix: Forms of Inferences |
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597 | (1) |
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26.B Appendix: Constructivism |
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598 | (2) |
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26.C Appendix: Bayes' Theorem and Some of Its Epistemological Aspects |
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600 | (1) |
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26.D Appendix: Modal and Amodal Completion or Perception |
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600 | (1) |
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26.E Appendix: Operational Constraints in Visual Processing |
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601 | (1) |
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602 | (3) |
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27 Diagrammatic Reasoning |
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605 | (14) |
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27.1 Cognitive Affordances of Diagrams and Visual Images |
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606 | (2) |
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27.2 Reasoning with Data Graphs |
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608 | (5) |
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27.3 Reasoning with Mechanism Diagrams |
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613 | (3) |
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27.4 Conclusions and Future Tasks |
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616 | (1) |
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617 | (2) |
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28 Embodied Mental Imagery in Cognitive Robots |
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619 | (20) |
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28.1 Mental Imagery Research Background |
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620 | (2) |
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28.2 Models and Approaches Based on Mental Imagery in Cognitive Systems and Robotics |
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622 | (2) |
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624 | (11) |
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635 | (1) |
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635 | (4) |
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29 Dynamical Models of Cognition |
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639 | (18) |
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639 | (2) |
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29.2 Data-Oriented Models |
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641 | (3) |
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29.3 Cognition and Action Distinct |
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644 | (4) |
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29.4 Cognition and Action Intrinsically Linked |
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648 | (5) |
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653 | (2) |
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655 | (2) |
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30 Complex versus Complicated Models of Cognition |
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657 | (14) |
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30.1 Current Views on Cognition |
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658 | (2) |
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30.2 Explaining Cognition |
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660 | (2) |
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30.3 Is Cognition Best Explained by a Complicated or Complex Model? |
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662 | (4) |
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666 | (1) |
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666 | (5) |
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31 From Neural Circuitry to Mechanistic Model-Based Reasoning |
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671 | (24) |
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31.1 Mechanistic Reasoning in Science |
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672 | (1) |
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31.2 The Psychology of Model-Based Reasoning |
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673 | (2) |
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31.3 Mental Models in the Brain: Attempts at Psycho-Neural Reduction |
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675 | (11) |
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31.4 Realization Story Applied |
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686 | (1) |
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31.5 Mechanistic Explanation Revisited |
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687 | (3) |
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690 | (1) |
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690 | (5) |
| Part G Modelling and Computational Issues |
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32 Computational Aspects of Model-Based Reasoning |
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695 | (24) |
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32.1 Computational Turn Seen from Different Perspectives |
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695 | (2) |
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32.2 Models of Computation |
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697 | (3) |
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32.3 Computation Versus Information |
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700 | (2) |
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32.4 The Difference Between Mathematical and Computational (Executable) Models |
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702 | (1) |
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32.5 Computation in the Wild |
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703 | (3) |
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32.6 Cognition: Knowledge Generation by Computation of New Information |
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706 | (3) |
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32.7 Model-Based Reasoning and Computational Automation of Reasoning |
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709 | (3) |
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32.8 Model Transformations and Semantics: Separation Between Semantics and Ontology |
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712 | (3) |
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715 | (4) |
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33 Computational Scientific Discovery |
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719 | (16) |
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33.1 The Roots of Human Scientific Discovery |
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720 | (1) |
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33.2 The Nature of Scientific Discovery |
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721 | (1) |
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33.3 The Psychology of Human Scientific Discovery |
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722 | (1) |
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33.4 Computational Discovery in Mathematics |
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723 | (2) |
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33.5 Methods and Applications in Computational Scientific Discovery |
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725 | (5) |
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730 | (1) |
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731 | (4) |
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34 Computer Simulations and Computational Models in Science |
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735 | (48) |
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34.1 Computer Simulations in Perspective |
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736 | (3) |
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34.2 The Variety of Computer Simulations and Computational Models |
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739 | (4) |
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34.3 Epistemology of Computational Models and Computer Simulations |
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743 | (7) |
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34.4 Computer Simulations, Explanation, and Understanding |
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750 | (8) |
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34.5 Comparing: Computer Simulations, Experiments and Thought Experiments |
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758 | (9) |
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34.6 The Definition of Computational Models and Simulations |
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767 | (6) |
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34.7 Conclusion: Human-Centered, but no Longer Human-Tailored Science |
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773 | (2) |
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775 | (8) |
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35 Simulation of Complex Systems |
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783 | (16) |
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783 | (2) |
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35.2 Modeling Complex Systems |
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785 | (4) |
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35.3 Agent-Based Simulation of Complex Systems |
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789 | (6) |
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35.4 Summing Up and Future Trends |
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795 | (1) |
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796 | (3) |
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36 Models and Experiments in Robotics |
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799 | (18) |
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36.1 A Conceptual Premise |
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799 | (2) |
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36.2 Experimental Issues in Robotics |
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801 | (1) |
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36.3 From Experimental Computer Science to Good Experimental Methodologies in Autonomous Robotics |
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802 | (2) |
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804 | (3) |
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36.5 Benchmarking and Standards |
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807 | (2) |
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36.6 Competitions and Challenges |
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809 | (3) |
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812 | (1) |
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812 | (5) |
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817 | (26) |
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37.1 Robots as Models of Living Systems |
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817 | (8) |
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37.2 A Short History of Biorobotics |
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825 | (1) |
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37.3 Methodological Issues |
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826 | (7) |
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833 | (1) |
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834 | (9) |
| Part H Models in Physics, Chemistry and Life Sciences |
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38 Comparing Symmetries in Models and Simulations |
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843 | (14) |
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844 | (1) |
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38.2 What Do Equations and Computations Do? |
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845 | (3) |
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38.3 Randomness in Biology |
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848 | (1) |
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38.4 Symmetries and Information in Physics and Biology |
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849 | (3) |
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38.5 Theoretical Symmetries and Randomness |
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852 | (2) |
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854 | (3) |
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39 Experimentation on Analogue Models |
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857 | (22) |
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39.1 Analogue Models: Terminology and Role |
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858 | (10) |
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39.2 Analogue Models in Physics |
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868 | (5) |
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39.3 Comparing Fundamental Bases for Physical Analogue Models |
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873 | (3) |
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876 | (1) |
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877 | (2) |
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40 Models of Chemical Structure |
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879 | (12) |
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40.1 Models, Theory, and Explanations in Structural Organic Chemistry |
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881 | (2) |
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40.2 Structures in the Applications of Chemistry |
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883 | (2) |
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40.3 The Dynamics of Structure |
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885 | (4) |
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889 | (2) |
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891 | (22) |
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41.1 What Are Geosciences? |
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891 | (1) |
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41.2 Conceptual Models in the Geosciences |
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892 | (1) |
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41.3 Physical Models in the Geosciences |
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893 | (2) |
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41.4 Numerical Models in the Geosciences |
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895 | (2) |
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41.5 Bringing the Social Sciences Into Geoscience Modeling |
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897 | (1) |
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41.6 Testing Models: From Calibration to Validation |
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898 | (4) |
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41.7 Inverse Problem Modeling |
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902 | (1) |
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41.8 Uncertainty in Geoscience Modeling |
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903 | (4) |
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41.9 Multimodel Approaches in Geosciences |
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907 | (1) |
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908 | (1) |
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908 | (5) |
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42 Models in the Biological Sciences |
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913 | (16) |
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913 | (9) |
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42.2 Confirmation in Evolutionary Biology |
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922 | (3) |
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42.3 Models in Behavioral Evolution and Ecology |
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925 | (2) |
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927 | (2) |
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43 Models and Mechanisms in Cognitive Science |
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929 | (24) |
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43.1 What is a Model in Cognitive Science? |
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929 | (11) |
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43.2 Open Problems in Computational Modeling |
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940 | (8) |
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948 | (1) |
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949 | (4) |
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44 Model-Based Reasoning in the Social Sciences |
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953 | (22) |
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44.1 Modeling Practices in the Social Sciences |
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954 | (4) |
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958 | (4) |
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962 | (1) |
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44.4 Models and Neighboring Concepts |
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963 | (4) |
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967 | (1) |
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968 | (7) |
| Part I Models in Engineering, Architecture, and Economical and Human Sciences |
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45 Models in Architectural Design |
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975 | (14) |
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45.1 Architectural Design Thinking |
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976 | (5) |
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45.2 BIM Models and Parametric Models |
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981 | (3) |
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45.3 Implementing and Using ICT for Design and Construction |
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984 | (3) |
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987 | (2) |
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46 Representational and Experimental Modeling in Archaeology |
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989 | (14) |
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46.1 Philosophical Resources and Archaeological Parallels |
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990 | (1) |
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46.2 The Challenges of Archaeological Modeling |
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991 | (1) |
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46.3 A Taxonomy of Archaeological Models |
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992 | (8) |
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1000 | (1) |
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1000 | (3) |
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47 Models and Ideology in Design |
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1003 | (12) |
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1003 | (1) |
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1004 | (1) |
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47.3 Revivalism: Looking to the Past |
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1005 | (1) |
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47.4 Modernism: Transcending History |
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1006 | (3) |
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47.5 Industrial Design: The Shape of Things to Come |
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1009 | (2) |
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1011 | (2) |
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1013 | (1) |
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1013 | (2) |
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48 Restructuring Incomplete Models in Innovators Marketplace on Data Jackets |
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1015 | (18) |
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48.1 Chance Discovery as a Trigger to Innovation |
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1016 | (1) |
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48.2 Chance Discovery from Data and Communication |
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1016 | (4) |
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48.3 IM for Externalizing and Connecting Requirements and Solutions |
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1020 | (2) |
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48.4 Innovators Marketplace on Data Jackets |
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1022 | (1) |
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48.5 IMDJ as Place for Reasoning on Incomplete Models |
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1023 | (6) |
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1029 | (1) |
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1029 | (4) |
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49 Models in Pedagogy and Education |
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1033 | (18) |
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1034 | (5) |
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1039 | (3) |
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1042 | (6) |
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1048 | (1) |
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1048 | (3) |
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50 Model-Based Reasoning in Crime Prevention |
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1051 | (14) |
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50.1 Ambient Intelligence |
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1053 | (1) |
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1054 | (1) |
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1055 | (3) |
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1058 | (2) |
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1060 | (1) |
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1060 | (2) |
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1062 | (1) |
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1062 | (3) |
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51 Modeling in the Macroeconomics of Financial Markets |
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|
1065 | (38) |
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51.1 The Intrinsic Instability of Financial Markets |
|
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1066 | (5) |
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51.2 The Financial Theory of Investment |
|
|
1071 | (3) |
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51.3 The Financial Instability Hypothesis Versus the Efficient Markets Hypothesis |
|
|
1074 | (1) |
|
51.4 Irving Fisher's Debt-Deflation Model |
|
|
1074 | (5) |
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51.5 Policy Implications and the Shareholder Maximization Value Model |
|
|
1079 | (6) |
|
51.6 Integrating the Minskyian Model with New Marxists and Social Structure of Accumulation (SSA) Theories |
|
|
1085 | (1) |
|
51.7 Risk and Uncertainty |
|
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1086 | (12) |
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1098 | (5) |
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52 Application of Models from Social Science to Social Policy |
|
|
1103 | (14) |
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|
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52.1 Unrealistic Assumptions |
|
|
1105 | (5) |
|
52.2 Real Experiments, Not Models Please! |
|
|
1110 | (5) |
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1115 | (1) |
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1116 | (1) |
|
53 Models and Moral Deliberation |
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|
1117 | (12) |
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1118 | (1) |
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1119 | (2) |
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1121 | (1) |
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1122 | (2) |
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1124 | (1) |
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1125 | (1) |
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|
1126 | (1) |
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|
1127 | (2) |
| About the Authors |
|
1129 | (12) |
| Detailed Contents |
|
1141 | (22) |
| Subject Index |
|
1163 | |
Lisainfo e-raamatute kohta