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Guided randomness in optimization / / Maurice Clerc
| Guided randomness in optimization / / Maurice Clerc |
| Autore | Clerc Maurice |
| Pubbl/distr/stampa | London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2015 |
| Descrizione fisica | 1 online resource (320 p.) |
| Disciplina | 519.3 |
| Collana | Computer Engineering Series. Metaheuristics Set |
| Soggetto topico | Mathematical optimization |
| ISBN |
1-119-13645-8
1-84821-805-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
""Cover""; ""Title Page""; ""Copyright""; ""Contents""; ""Preface""; ""About this book""; ""Organization of the book""; ""Tools""; ""Key points""; ""Contact the author""; ""Introduction""; ""PART 1: Randomness in Optimization""; ""1: Necessary Risk""; ""1.1. No better than random search""; ""1.1.1. Uniform random search""; ""1.1.2. Sequential search""; ""1.1.3. Partial gradient""; ""1.2. Better or worse than random search""; ""1.2.1. Positive correlation problems""; ""1.2.2. Negative correlation problems""; ""2: Random Number Generators (RNGs)""; ""2.1. Generator types""
""3.3. Distribution of the Next Possible Positions (DNPP)""""3.4. Confinement, constraints and repairs""; ""3.4.1. Strict confinement""; ""3.4.2. Random confinement""; ""3.4.3. Moderate confinement""; ""3.4.4. Reverse""; ""3.4.5. Reflection-diffusion""; ""3.5. Strategy selection""; ""PART 2: Optimizer Comparison""; ""Introduction to Part 2""; ""4: Algorithms and Optimizers""; ""4.1. The Minimaliste algorithm""; ""4.1.1. General description""; ""4.1.2. Minimaliste in practice""; ""4.1.3. Use of randomness""; ""4.2. PSO""; ""4.2.1. Description""; ""4.2.2. Use of randomness""; ""4.3. APS"" ""4.3.1. Description""""4.3.2. Uses of randomness""; ""4.4. Applications of randomness""; ""5: Performance Criteria""; ""5.1. Eff-Res: construction and properties""; ""5.1.1. Simple example using random search""; ""5.2. Criteria and measurements""; ""5.2.1. Objective criteria""; ""5.2.1.1. Result probabilities""; ""5.2.1.2. Effort probabilities""; ""5.2.1.3. Mean result of an effort""; ""5.2.1.4. Median result of an effort""; ""5.2.1.5. Normalized efficiency""; ""5.2.1.6. Mean and median cost""; ""5.2.2. Semi-subjective criteria""; ""5.2.2.1. Fragmentation of effort"" ""5.2.2.2. Result quality and success rate""""5.2.2.3. Global quality""; ""5.3. Practical construction of an Eff-Res""; ""5.3.1. Detailed example: (Minimaliste, Alpine 2D)""; ""5.3.2. Qualitative interpretations""; ""5.4. Conclusion""; ""6: Comparing Optimizers""; ""6.1. Data collection and preprocessing""; ""6.2. Critical analysis of comparisons""; ""6.2.1. Influence of criteria and the number of attempts""; ""6.2.2. Influence of effort levels""; ""6.2.3. Global comparison""; ""6.2.4. Influence of the RNG""; ""6.3. Uncertainty in statistical analysis""; ""6.3.1. Independence of tests"" ""6.3.2. Confidence threshold"" |
| Record Nr. | UNINA-9910131289603321 |
Clerc Maurice
|
||
| London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Guided randomness in optimization / / Maurice Clerc
| Guided randomness in optimization / / Maurice Clerc |
| Autore | Clerc Maurice |
| Pubbl/distr/stampa | London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2015 |
| Descrizione fisica | 1 online resource (320 p.) |
| Disciplina | 519.3 |
| Collana | Computer Engineering Series. Metaheuristics Set |
| Soggetto topico | Mathematical optimization |
| ISBN |
1-119-13645-8
1-84821-805-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
""Cover""; ""Title Page""; ""Copyright""; ""Contents""; ""Preface""; ""About this book""; ""Organization of the book""; ""Tools""; ""Key points""; ""Contact the author""; ""Introduction""; ""PART 1: Randomness in Optimization""; ""1: Necessary Risk""; ""1.1. No better than random search""; ""1.1.1. Uniform random search""; ""1.1.2. Sequential search""; ""1.1.3. Partial gradient""; ""1.2. Better or worse than random search""; ""1.2.1. Positive correlation problems""; ""1.2.2. Negative correlation problems""; ""2: Random Number Generators (RNGs)""; ""2.1. Generator types""
""3.3. Distribution of the Next Possible Positions (DNPP)""""3.4. Confinement, constraints and repairs""; ""3.4.1. Strict confinement""; ""3.4.2. Random confinement""; ""3.4.3. Moderate confinement""; ""3.4.4. Reverse""; ""3.4.5. Reflection-diffusion""; ""3.5. Strategy selection""; ""PART 2: Optimizer Comparison""; ""Introduction to Part 2""; ""4: Algorithms and Optimizers""; ""4.1. The Minimaliste algorithm""; ""4.1.1. General description""; ""4.1.2. Minimaliste in practice""; ""4.1.3. Use of randomness""; ""4.2. PSO""; ""4.2.1. Description""; ""4.2.2. Use of randomness""; ""4.3. APS"" ""4.3.1. Description""""4.3.2. Uses of randomness""; ""4.4. Applications of randomness""; ""5: Performance Criteria""; ""5.1. Eff-Res: construction and properties""; ""5.1.1. Simple example using random search""; ""5.2. Criteria and measurements""; ""5.2.1. Objective criteria""; ""5.2.1.1. Result probabilities""; ""5.2.1.2. Effort probabilities""; ""5.2.1.3. Mean result of an effort""; ""5.2.1.4. Median result of an effort""; ""5.2.1.5. Normalized efficiency""; ""5.2.1.6. Mean and median cost""; ""5.2.2. Semi-subjective criteria""; ""5.2.2.1. Fragmentation of effort"" ""5.2.2.2. Result quality and success rate""""5.2.2.3. Global quality""; ""5.3. Practical construction of an Eff-Res""; ""5.3.1. Detailed example: (Minimaliste, Alpine 2D)""; ""5.3.2. Qualitative interpretations""; ""5.4. Conclusion""; ""6: Comparing Optimizers""; ""6.1. Data collection and preprocessing""; ""6.2. Critical analysis of comparisons""; ""6.2.1. Influence of criteria and the number of attempts""; ""6.2.2. Influence of effort levels""; ""6.2.3. Global comparison""; ""6.2.4. Influence of the RNG""; ""6.3. Uncertainty in statistical analysis""; ""6.3.1. Independence of tests"" ""6.3.2. Confidence threshold"" |
| Record Nr. | UNINA-9910822961703321 |
|
Clerc Maurice
|
||
| London, England ; ; Hoboken, New Jersey : , : ISTE : , : Wiley, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Iterative optimizers : difficulty measures and benchmarks / / Maurice Clerc
| Iterative optimizers : difficulty measures and benchmarks / / Maurice Clerc |
| Autore | Clerc Maurice |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : ISTE : , : Wiley, , 2019 |
| Descrizione fisica | 1 online resource (215 pages) |
| Disciplina | 519.3 |
| Soggetto topico | Mathematical optimization |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-119-61240-3
1-119-61247-0 1-119-61236-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910554815203321 |
|
Clerc Maurice
|
||
| Hoboken, New Jersey : , : ISTE : , : Wiley, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Iterative optimizers : difficulty measures and benchmarks / / Maurice Clerc
| Iterative optimizers : difficulty measures and benchmarks / / Maurice Clerc |
| Autore | Clerc Maurice |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : ISTE : , : Wiley, , 2019 |
| Descrizione fisica | 1 online resource (215 pages) |
| Disciplina | 519.3 |
| Soggetto topico | Mathematical optimization |
| ISBN |
1-119-61240-3
1-119-61247-0 1-119-61236-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910830755503321 |
|
Clerc Maurice
|
||
| Hoboken, New Jersey : , : ISTE : , : Wiley, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Optimiseurs Itératifs
| Optimiseurs Itératifs |
| Autore | Clerc Maurice |
| Pubbl/distr/stampa | London : , : ISTE Editions Ltd., , 2019 |
| Descrizione fisica | 1 online resource (189 pages) |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-78406-579-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Nota di contenuto | Cover -- Table des matières -- Avant-propos. L'essentiel -- Introduction -- Chapitre 1. Quelques définitions -- Chapitre 2. Difficulté de la difficulté -- Chapitre 3. Typologie des paysages -- Chapitre 4. Le programme LandGener -- Chapitre 5. Jeux d'essai -- Chapitre 6. Difficulté versus dimension -- Chapitre 7. Exploitation et explorationversus difficulté -- Chapitre 8. L'algorithme Explo2 -- Chapitre 9. Balance et difficulté perçue -- Annexe -- Bibliographie -- Index. |
| Record Nr. | UNINA-9910493161203321 |
|
Clerc Maurice
|
||
| London : , : ISTE Editions Ltd., , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Optimiseurs itératifs : mesures de difficulté et jeux d'essai / / Maurice Clerc
| Optimiseurs itératifs : mesures de difficulté et jeux d'essai / / Maurice Clerc |
| Autore | Clerc Maurice |
| Pubbl/distr/stampa | London, England : , : ISTE Editions, , [2019] |
| Descrizione fisica | 1 online resource (189 pages) |
| Disciplina | 519.3 |
| Collana | Collection informatique |
| Soggetto topico | Mathematical optimization |
| ISBN | 1-78406-579-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Nota di contenuto | Cover -- Table des matières -- Avant-propos. L'essentiel -- Introduction -- Chapitre 1. Quelques définitions -- Chapitre 2. Difficulté de la difficulté -- Chapitre 3. Typologie des paysages -- Chapitre 4. Le programme LandGener -- Chapitre 5. Jeux d'essai -- Chapitre 6. Difficulté versus dimension -- Chapitre 7. Exploitation et explorationversus difficulté -- Chapitre 8. L'algorithme Explo2 -- Chapitre 9. Balance et difficulté perçue -- Annexe -- Bibliographie -- Index. |
| Record Nr. | UNINA-9910793558203321 |
|
Clerc Maurice
|
||
| London, England : , : ISTE Editions, , [2019] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Optimiseurs itératifs : mesures de difficulté et jeux d'essai / / Maurice Clerc
| Optimiseurs itératifs : mesures de difficulté et jeux d'essai / / Maurice Clerc |
| Autore | Clerc Maurice |
| Pubbl/distr/stampa | London, England : , : ISTE Editions, , [2019] |
| Descrizione fisica | 1 online resource (189 pages) |
| Disciplina | 519.3 |
| Collana | Collection informatique |
| Soggetto topico | Mathematical optimization |
| ISBN | 1-78406-579-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Nota di contenuto | Cover -- Table des matières -- Avant-propos. L'essentiel -- Introduction -- Chapitre 1. Quelques définitions -- Chapitre 2. Difficulté de la difficulté -- Chapitre 3. Typologie des paysages -- Chapitre 4. Le programme LandGener -- Chapitre 5. Jeux d'essai -- Chapitre 6. Difficulté versus dimension -- Chapitre 7. Exploitation et explorationversus difficulté -- Chapitre 8. L'algorithme Explo2 -- Chapitre 9. Balance et difficulté perçue -- Annexe -- Bibliographie -- Index. |
| Record Nr. | UNINA-9910825592803321 |
|
Clerc Maurice
|
||
| London, England : , : ISTE Editions, , [2019] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Particle swarm optimization / / Maurice Clerc
| Particle swarm optimization / / Maurice Clerc |
| Autore | Clerc Maurice |
| Pubbl/distr/stampa | London ; ; Newport Beach : , : ISTE, , 2006 |
| Descrizione fisica | 1 online resource (245 pages) |
| Disciplina |
006.3
519.62 |
| Collana | ISTE |
| Soggetto topico |
Mathematical optimization
Particles (Nuclear physics) Swarm intelligence |
| Soggetto genere / forma | Electronic books. |
| ISBN |
9780470612163
9786610510566 1-84704-454-9 0-470-61216-9 0-470-39443-9 1-84704-554-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Particle Swarm Optimization; Table of Contents; Foreword; Introduction; Part I. Particle Swarm Optimization; Chapter 1. What is a Difficult Problem?; 1.1. An intrinsic definition.; 1.2. Estimation and practical measurement.; 1.3. For "amatheurs": some estimates of difficulty; 1.3.1. Function xd; 1.3.2. Function x2d; 1.3.3. Function xd|sin(xd)|; 1.3.4. Traveling salesman on D cities; 1.4. Summary; Chapter 2. On a Table Corner; 2.1. Apiarian metaphor; 2.2. An aside on the spreading of a rumor; 2.3. Abstract formulation; 2.4. What is really transmitted; 2.5. Cooperation versus competition; 2.6. For "amatheurs": a simple calculation of propagation of rumor2.7. Summary; Chapter 3. First Formulations; 3.1. Minimal version; 3.1.1. Swarm size; 3.1.2. Information links; 3.1.3. Initialization; 3.1.4. Equations of motion; 3.1.5. Interval confinement; 3.1.6. Proximity distributions; 3.2. Two common errors; 3.3. Principal drawbacks of this formulation; 3.3.1. Distribution bias; 3.3.2. Explosion and maximum velocity; 3.4. Manual parameter setting; 3.5. For "amatheurs": average number of informants; 3.6. Summary; Chapter 4. Benchmark Set; 4.1. What is the purpose of test functions?; 4.2. Six reference functions4.3. Representations and comments; 4.4. For "amatheurs": estimates of levels of difficulty; 4.4.1. Theoretical difficulty; 4.4.1.1. Tripod; 4.4.1.2. Alpine 10D; 4.4.1.3. Rosenbrock; 4.4.2. Difficulty according to the search effort; 4.5. Summary; Chapter 5. Mistrusting Chance; 5.1. Analysis of an anomaly; 5.2. Computing randomness; 5.3. Reproducibility; 5.4. On numerical precision; 5.5. The rare KISS; 5.5.1. Brief description; 5.5.2. Test of KISS; 5.6. On the comparison of results; 5.7. For "amatheurs": confidence in the estimate of a rate of failure; 5.8. C programs5.9. Summary; Chapter 6. First Results; 6.1. A simple program; 6.2. Overall results; 6.3. Robustness and performance maps; 6.4. Theoretical difficulty and noted difficulty; 6.5. Source code of OEP 0; 6.6. Summary; Chapter 7. Swarm: Memory and Graphs of Influence; 7.1. Circular neighborhood of the historical PSO; 7.2. Memory-swarm; 7.3. Fixed topologies; 7.4. Random variable topologies; 7.4.1. Direct recruitment; 7.4.2. Recruitment by common channel of communication; 7.5. Influence of the number of informants; 7.5.1. In fixed topology; 7.5.2. In random variable topology; 7.6. Influence of the number of memories7.7. Reorganizations of the memory-swarm; 7.7.1. Mixing of the memories; 7.7.2. Queen and other centroids; 7.7.3. Comparative results; 7.8. For "amatheurs": temporal connectivity in random recruitment; 7.9. Summary; Chapter 8. Distributions of Proximity; 8.1. The random possibilities; 8.2. Review of rectangular distribution; 8.3. Alternative distributions of possibilities; 8.3.1. Ellipsoidal positive sectors; 8.3.2. Independent Gaussians; 8.3.3. Local by independent Gaussians; 8.3.4. The class of one-dimensional distributions; 8.3.5. Pivots; 8.3.6. Adjusted ellipsoids |
| Record Nr. | UNINA-9910143311203321 |
|
Clerc Maurice
|
||
| London ; ; Newport Beach : , : ISTE, , 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Particle swarm optimization / / Maurice Clerc
| Particle swarm optimization / / Maurice Clerc |
| Autore | Clerc Maurice |
| Pubbl/distr/stampa | London ; ; Newport Beach : , : ISTE, , 2006 |
| Descrizione fisica | 1 online resource (245 pages) |
| Disciplina |
006.3
519.62 |
| Collana | ISTE |
| Soggetto topico |
Mathematical optimization
Particles (Nuclear physics) Swarm intelligence |
| ISBN |
9780470612163
9786610510566 1-84704-454-9 0-470-61216-9 0-470-39443-9 1-84704-554-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Particle Swarm Optimization; Table of Contents; Foreword; Introduction; Part I. Particle Swarm Optimization; Chapter 1. What is a Difficult Problem?; 1.1. An intrinsic definition.; 1.2. Estimation and practical measurement.; 1.3. For "amatheurs": some estimates of difficulty; 1.3.1. Function xd; 1.3.2. Function x2d; 1.3.3. Function xd|sin(xd)|; 1.3.4. Traveling salesman on D cities; 1.4. Summary; Chapter 2. On a Table Corner; 2.1. Apiarian metaphor; 2.2. An aside on the spreading of a rumor; 2.3. Abstract formulation; 2.4. What is really transmitted; 2.5. Cooperation versus competition; 2.6. For "amatheurs": a simple calculation of propagation of rumor2.7. Summary; Chapter 3. First Formulations; 3.1. Minimal version; 3.1.1. Swarm size; 3.1.2. Information links; 3.1.3. Initialization; 3.1.4. Equations of motion; 3.1.5. Interval confinement; 3.1.6. Proximity distributions; 3.2. Two common errors; 3.3. Principal drawbacks of this formulation; 3.3.1. Distribution bias; 3.3.2. Explosion and maximum velocity; 3.4. Manual parameter setting; 3.5. For "amatheurs": average number of informants; 3.6. Summary; Chapter 4. Benchmark Set; 4.1. What is the purpose of test functions?; 4.2. Six reference functions4.3. Representations and comments; 4.4. For "amatheurs": estimates of levels of difficulty; 4.4.1. Theoretical difficulty; 4.4.1.1. Tripod; 4.4.1.2. Alpine 10D; 4.4.1.3. Rosenbrock; 4.4.2. Difficulty according to the search effort; 4.5. Summary; Chapter 5. Mistrusting Chance; 5.1. Analysis of an anomaly; 5.2. Computing randomness; 5.3. Reproducibility; 5.4. On numerical precision; 5.5. The rare KISS; 5.5.1. Brief description; 5.5.2. Test of KISS; 5.6. On the comparison of results; 5.7. For "amatheurs": confidence in the estimate of a rate of failure; 5.8. C programs5.9. Summary; Chapter 6. First Results; 6.1. A simple program; 6.2. Overall results; 6.3. Robustness and performance maps; 6.4. Theoretical difficulty and noted difficulty; 6.5. Source code of OEP 0; 6.6. Summary; Chapter 7. Swarm: Memory and Graphs of Influence; 7.1. Circular neighborhood of the historical PSO; 7.2. Memory-swarm; 7.3. Fixed topologies; 7.4. Random variable topologies; 7.4.1. Direct recruitment; 7.4.2. Recruitment by common channel of communication; 7.5. Influence of the number of informants; 7.5.1. In fixed topology; 7.5.2. In random variable topology; 7.6. Influence of the number of memories7.7. Reorganizations of the memory-swarm; 7.7.1. Mixing of the memories; 7.7.2. Queen and other centroids; 7.7.3. Comparative results; 7.8. For "amatheurs": temporal connectivity in random recruitment; 7.9. Summary; Chapter 8. Distributions of Proximity; 8.1. The random possibilities; 8.2. Review of rectangular distribution; 8.3. Alternative distributions of possibilities; 8.3.1. Ellipsoidal positive sectors; 8.3.2. Independent Gaussians; 8.3.3. Local by independent Gaussians; 8.3.4. The class of one-dimensional distributions; 8.3.5. Pivots; 8.3.6. Adjusted ellipsoids |
| Record Nr. | UNISA-996217137603316 |
|
Clerc Maurice
|
||
| London ; ; Newport Beach : , : ISTE, , 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Particle swarm optimization / / Maurice Clerc
| Particle swarm optimization / / Maurice Clerc |
| Autore | Clerc Maurice |
| Pubbl/distr/stampa | London ; ; Newport Beach, : ISTE, 2006 |
| Descrizione fisica | 1 online resource (245 pages) |
| Disciplina | 539.7/2 |
| Collana | ISTE |
| Soggetto topico |
Mathematical optimization
Particles (Nuclear physics) Swarm intelligence |
| ISBN |
9780470612163
9786610510566 1-84704-454-9 0-470-61216-9 0-470-39443-9 1-84704-554-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Particle Swarm Optimization; Table of Contents; Foreword; Introduction; Part I. Particle Swarm Optimization; Chapter 1. What is a Difficult Problem?; 1.1. An intrinsic definition.; 1.2. Estimation and practical measurement.; 1.3. For "amatheurs": some estimates of difficulty; 1.3.1. Function xd; 1.3.2. Function x2d; 1.3.3. Function xd|sin(xd)|; 1.3.4. Traveling salesman on D cities; 1.4. Summary; Chapter 2. On a Table Corner; 2.1. Apiarian metaphor; 2.2. An aside on the spreading of a rumor; 2.3. Abstract formulation; 2.4. What is really transmitted; 2.5. Cooperation versus competition; 2.6. For "amatheurs": a simple calculation of propagation of rumor2.7. Summary; Chapter 3. First Formulations; 3.1. Minimal version; 3.1.1. Swarm size; 3.1.2. Information links; 3.1.3. Initialization; 3.1.4. Equations of motion; 3.1.5. Interval confinement; 3.1.6. Proximity distributions; 3.2. Two common errors; 3.3. Principal drawbacks of this formulation; 3.3.1. Distribution bias; 3.3.2. Explosion and maximum velocity; 3.4. Manual parameter setting; 3.5. For "amatheurs": average number of informants; 3.6. Summary; Chapter 4. Benchmark Set; 4.1. What is the purpose of test functions?; 4.2. Six reference functions4.3. Representations and comments; 4.4. For "amatheurs": estimates of levels of difficulty; 4.4.1. Theoretical difficulty; 4.4.1.1. Tripod; 4.4.1.2. Alpine 10D; 4.4.1.3. Rosenbrock; 4.4.2. Difficulty according to the search effort; 4.5. Summary; Chapter 5. Mistrusting Chance; 5.1. Analysis of an anomaly; 5.2. Computing randomness; 5.3. Reproducibility; 5.4. On numerical precision; 5.5. The rare KISS; 5.5.1. Brief description; 5.5.2. Test of KISS; 5.6. On the comparison of results; 5.7. For "amatheurs": confidence in the estimate of a rate of failure; 5.8. C programs5.9. Summary; Chapter 6. First Results; 6.1. A simple program; 6.2. Overall results; 6.3. Robustness and performance maps; 6.4. Theoretical difficulty and noted difficulty; 6.5. Source code of OEP 0; 6.6. Summary; Chapter 7. Swarm: Memory and Graphs of Influence; 7.1. Circular neighborhood of the historical PSO; 7.2. Memory-swarm; 7.3. Fixed topologies; 7.4. Random variable topologies; 7.4.1. Direct recruitment; 7.4.2. Recruitment by common channel of communication; 7.5. Influence of the number of informants; 7.5.1. In fixed topology; 7.5.2. In random variable topology; 7.6. Influence of the number of memories7.7. Reorganizations of the memory-swarm; 7.7.1. Mixing of the memories; 7.7.2. Queen and other centroids; 7.7.3. Comparative results; 7.8. For "amatheurs": temporal connectivity in random recruitment; 7.9. Summary; Chapter 8. Distributions of Proximity; 8.1. The random possibilities; 8.2. Review of rectangular distribution; 8.3. Alternative distributions of possibilities; 8.3.1. Ellipsoidal positive sectors; 8.3.2. Independent Gaussians; 8.3.3. Local by independent Gaussians; 8.3.4. The class of one-dimensional distributions; 8.3.5. Pivots; 8.3.6. Adjusted ellipsoids |
| Record Nr. | UNINA-9910877533503321 |
|
Clerc Maurice
|
||
| London ; ; Newport Beach, : ISTE, 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||