The Design of Innovation: Lessons from and for Competent Genetic Algorithms
7 69 6 A DESIGN APPROACH TO PROBLEM DIFFICULTY 71 1 Design and Problem Difficulty 71 2 Three Misconceptions 72 3 Hard Problems Exist 76 4 The 3-Way Decomposition and Its Core 77 The Core of Intra-BB Difficulty: Deception 5 77 6 The Core of Inter-BB Difficulty: Scaling 83 7 The Core of Extra-BB Diffi...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Springer US
2002
|
| Ausgabe: | 1st ed. 2002 |
| Schriftenreihe: | Genetic Algorithms and Evolutionary Computation
7 |
| Schlagworte: | |
| Online-Zugang: | UBY01 Volltext |
| Zusammenfassung: | 7 69 6 A DESIGN APPROACH TO PROBLEM DIFFICULTY 71 1 Design and Problem Difficulty 71 2 Three Misconceptions 72 3 Hard Problems Exist 76 4 The 3-Way Decomposition and Its Core 77 The Core of Intra-BB Difficulty: Deception 5 77 6 The Core of Inter-BB Difficulty: Scaling 83 7 The Core of Extra-BB Difficulty: Noise 88 Crosstalk: All Roads Lead to the Core 8 89 9 From Multimodality to Hierarchy 93 10 Summary 100 7 ENSURING BUILDING BLOCK SUPPLY 101 1 Past Work 101 2 Facetwise Supply Model I: One BB 102 Facetwise Supply Model II: Partition Success 103 3 4 Population Size for BB Supply 104 Summary 5 106 8 ENSURING BUILDING BLOCK GROWTH 109 1 The Schema Theorem: BB Growth Bound 109 2 Schema Growth Somewhat More Generally 111 3 Designing for BB Market Share Growth 112 4 Selection Press ure for Early Success 114 5 Designing for Late in the Day 116 The Schema Theorem Works 6 118 A Demonstration of Selection Stall 7 119 Summary 122 8 9 MAKING TIME FOR BUILDING BLOCKS 125 1 Analysis of Selection Alone: Takeover Time 126 2 Drift: When Selection Chooses for No Reason 129 3 Convergence Times with Multiple BBs 132 4 A Time-Scales Derivation of Critical Locus 142 5 A Little Model of Noise-Induced Run Elongation 143 6 From Alleles to Building Blocks 147 7 Summary 148 10 DECIDING WELL 151 1 Why is Decision Making a Problem? 151 |
| Beschreibung: | 1 Online-Ressource (XXIV, 248 p) |
| ISBN: | 9781475736434 |
| DOI: | 10.1007/978-1-4757-3643-4 |
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| spelling | Goldberg, David E. Verfasser aut The Design of Innovation Lessons from and for Competent Genetic Algorithms by David E. Goldberg 1st ed. 2002 New York, NY Springer US 2002 1 Online-Ressource (XXIV, 248 p) txt rdacontent c rdamedia cr rdacarrier Genetic Algorithms and Evolutionary Computation 7 7 69 6 A DESIGN APPROACH TO PROBLEM DIFFICULTY 71 1 Design and Problem Difficulty 71 2 Three Misconceptions 72 3 Hard Problems Exist 76 4 The 3-Way Decomposition and Its Core 77 The Core of Intra-BB Difficulty: Deception 5 77 6 The Core of Inter-BB Difficulty: Scaling 83 7 The Core of Extra-BB Difficulty: Noise 88 Crosstalk: All Roads Lead to the Core 8 89 9 From Multimodality to Hierarchy 93 10 Summary 100 7 ENSURING BUILDING BLOCK SUPPLY 101 1 Past Work 101 2 Facetwise Supply Model I: One BB 102 Facetwise Supply Model II: Partition Success 103 3 4 Population Size for BB Supply 104 Summary 5 106 8 ENSURING BUILDING BLOCK GROWTH 109 1 The Schema Theorem: BB Growth Bound 109 2 Schema Growth Somewhat More Generally 111 3 Designing for BB Market Share Growth 112 4 Selection Press ure for Early Success 114 5 Designing for Late in the Day 116 The Schema Theorem Works 6 118 A Demonstration of Selection Stall 7 119 Summary 122 8 9 MAKING TIME FOR BUILDING BLOCKS 125 1 Analysis of Selection Alone: Takeover Time 126 2 Drift: When Selection Chooses for No Reason 129 3 Convergence Times with Multiple BBs 132 4 A Time-Scales Derivation of Critical Locus 142 5 A Little Model of Noise-Induced Run Elongation 143 6 From Alleles to Building Blocks 147 7 Summary 148 10 DECIDING WELL 151 1 Why is Decision Making a Problem? 151 Theory of Computation Artificial Intelligence Optimization Statistics, general Computers Artificial intelligence Mathematical optimization Statistics Erscheint auch als Druck-Ausgabe 9781475736458 Erscheint auch als Druck-Ausgabe 9781402070983 Erscheint auch als Druck-Ausgabe 9781475736441 https://doi.org/10.1007/978-1-4757-3643-4 Verlag URL des Eerstveröffentlichers Volltext |
| spellingShingle | Goldberg, David E. The Design of Innovation Lessons from and for Competent Genetic Algorithms Theory of Computation Artificial Intelligence Optimization Statistics, general Computers Artificial intelligence Mathematical optimization Statistics |
| title | The Design of Innovation Lessons from and for Competent Genetic Algorithms |
| title_auth | The Design of Innovation Lessons from and for Competent Genetic Algorithms |
| title_exact_search | The Design of Innovation Lessons from and for Competent Genetic Algorithms |
| title_exact_search_txtP | The Design of Innovation Lessons from and for Competent Genetic Algorithms |
| title_full | The Design of Innovation Lessons from and for Competent Genetic Algorithms by David E. Goldberg |
| title_fullStr | The Design of Innovation Lessons from and for Competent Genetic Algorithms by David E. Goldberg |
| title_full_unstemmed | The Design of Innovation Lessons from and for Competent Genetic Algorithms by David E. Goldberg |
| title_short | The Design of Innovation |
| title_sort | the design of innovation lessons from and for competent genetic algorithms |
| title_sub | Lessons from and for Competent Genetic Algorithms |
| topic | Theory of Computation Artificial Intelligence Optimization Statistics, general Computers Artificial intelligence Mathematical optimization Statistics |
| topic_facet | Theory of Computation Artificial Intelligence Optimization Statistics, general Computers Artificial intelligence Mathematical optimization Statistics |
| url | https://doi.org/10.1007/978-1-4757-3643-4 |
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