| Preface
 Sample Chapter - Download PDF (22 KB) | |
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| 1 | The Machine That Could Learn Anything
Sample Chapter - Download PDF (151 KB) | |
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| | 1.1 | Back to Reality | |
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| | 1.2 | Prediction Games | |
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| | 1.3 | Supervised Learning | |
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| | 1.4 | Concept and Classification Learning | |
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| | 1.5 | Behavior Learning | |
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| | 1.6 | Financial Prediction | |
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| | 1.7 | Learning Problems to Solve by Hand | |
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| | 1.8 | A Reasonable Learning Criterion | |
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| | 1.9 | Note | |
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| 2 | Consider Thy Neighbor | |
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| | 2.1 | Similarity and the Nearest-Neighbor Method | |
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| | 2.2 | Nearest-Neighbors in Picture Form | |
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| | 2.3 | Measuring Similarity and Distance | |
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| | 2.4 | Using 1-NN to Predict the Voting Behavior of Politicians | |
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| | 2.5 | General Performance of 1-NN Learning | |
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| | 2.6 | Warehouse Security Example: Eliminating False Alarms | |
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| | 2.7 | Notes | |
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| 3 | Kepler on Mars | |
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| | 3.1 | Science as Communal Learning | |
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| | 3.2 | Puzzling Under the Night Sky | |
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| | 3.3 | Kepler's Vital Statistics | |
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| | 3.4 | The Mysterium Cosmographicum | |
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| | 3.5 | Kepler and Tycho Brahe | |
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| | 3.6 | Getting It Right for the Wrong Reasons | |
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| | 3.7 | A Footnote on Neptune | |
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| | 3.8 | Lessons from Kepler | |
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| | 3.9 | Notes | |
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| 4 | The Information Chicane | |
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| | 4.1 | Information Theory: Starter Pack | |
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| | 4.2 | Uncertainty | |
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| | 4.3 | Redundancy | |
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| | 4.4 | Information in Bits | |
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| | 4.5 | Using Redundancy to Combat Noise | |
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| | 4.6 | Regularity as Useful Redundancy | |
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| | 4.7 | Notes | |
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| 5 | Fence-and-Fill Learning | |
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| | 5.1 | k-Means Clustering | |
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| | 5.2 | On-line k-means Clustering (Competitive Learning) | |
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| | 5.3 | Fence-and-Fill Learning | |
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| | 5.4 | Perception Learning | |
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| | 5.5 | Backpropagation and the Multilayer Perception | |
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| | 5.6 | Radial-Basis Functions | |
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| | 5.7 | ID3 and C4.5 | |
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| | 5.8 | The Naive Bayes Classifier | |
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| | 5.9 | Centre Splitting | |
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| | 5.10 | Boundaries of the Fence-and-Fill Class | |
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| | 5.11 | Warehouse Security Example (Continued): 24-Hour Crisis | |
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| | 5.12 | Notes | |
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| 6 | Turing and the Submarines | |
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| | 6.1 | Moonlight Sonata | |
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| | 6.2 | From Encryption to Decryption | |
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| | 6.3 | Encryption Using Keys | |
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| | 6.4 | Decryption Issues | |
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| | 6.5 | Public-Key Encryption and the RSA Method | |
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| | 6.6 | The Origins of Enigma | |
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| | 6.7 | Building Bombes | |
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| | 6.8 | Encryption and Learning | |
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| | 6.9 | Notes | |
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| 7 | The Relational Gulf | |
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| | 7.1 | A Meeting at the Crown | |
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| | 7.2 | Factor X: The Real Enigma | |
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| | 7.3 | The Explicitness Distinction | |
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| | 7.4 | Nonrelational Learning Is Similarity-Based Learning | |
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| | 7.5 | Incidental Effects | |
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| | 7.6 | Geometric Separability | |
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| | 7.7 | Alignment and Salience | |
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| | 7.8 | Sensation Entropy | |
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| | 7.9 | Notes | |
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| 8 | The Supercharged Learner | |
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| | 8.1 | The Relational/Nonrelational Continuum | |
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| | 8.2 | Sneaky Problems | |
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| | 8.3 | Supercharging | |
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| | 8.4 | The Need for Relational Partitions | |
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| | 8.5 | Pick-and-Mix Learning and Kepler's Third Law | |
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| | 8.6 | FOIL | |
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| | 8.7 | Relational Dilemma | |
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| | 8.8 | Warehouse Security Example--Third Installment | |
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| | 8.9 | Notes | |
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| 9 | David Hume and the Crash of '87 | |
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| | 9.1 | Ride a White Swan | |
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| | 9.2 | The Problem with Science | |
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| | 9.3 | Recovering from Hume's Crash | |
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| | 9.4 | Scandalous Philosophers | |
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| | 9.5 | Abolition of the Free Lunch | |
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| | 9.6 | Escape Clause | |
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| | 9.7 | Notes | |
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| 10 | Phases of Compression | |
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| | 10.1 | Through a Double Slit Darkly | |
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| | 10.2 | Induction--Compression Duality | |
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| | 10.3 | Data Compression | |
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| | 10.4 | Sequence Encoding and Ziv-Lempel Compression | |
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| | 10.5 | Kolmogorov Complexity and the (Mythical) Perfect Compressor | |
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| | 10.6 | Randomness | |
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| | 10.7 | Minimum Description Length | |
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| | 10.8 | Compression Phases | |
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| | 10.9 | Hume Slashed by Occam's Razor | |
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| | 10.10 | Notes | |
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| 11 | Protorepresentational Learning | |
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| | 11.1 | The Cincinnati Story | |
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| | 11.2 | Relational Learning Revisited | |
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| | 11.3 | Truth from Trash | |
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| | 11.4 | Why TFT Is Not Just Supercharged Fence-and-Fill | |
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| | 11.5 | From Virtual Sensors to Symbol Processing | |
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| | 11.6 | SCIL Learning--a Simple TFT Approach | |
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| | 11.7 | SCIL Learning in the Warehouse Domain | |
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| | 11.8 | Representational Implications | |
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| | 11.9 | Is TFT Nouvelle or Classical? | |
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| | 11.10 | Notes | |
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| 12 | The Creativity Continuum | |
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| | 12.1 | Cincinnati Postscript | |
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| | 12.2 | Crash Landing at Gatwick | |
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| | 12.3 | Demise of the Career Scientist | |
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| | 12.4 | Stop Press | |
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| | 12.5 | Notes | |
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| References | |
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| Index
Sample Chapter - Download PDF (19 KB) | |
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