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Designing intelligent machines . Volume 2 Concepts in artificial intelligence [[electronic resource] /] / by Jeffrey Johnson and Philip Picton
| Designing intelligent machines . Volume 2 Concepts in artificial intelligence [[electronic resource] /] / by Jeffrey Johnson and Philip Picton |
| Autore | Johnson Jeffrey |
| Pubbl/distr/stampa | Boston ; ; Oxford, : Butterworth-Heinemann in association with the Open University, 1995 |
| Descrizione fisica | 1 online resource (393 p.) |
| Disciplina |
621
629.89 |
| Altri autori (Persone) | PictonPhilip |
| Soggetto topico |
Mechatronics - Study and teaching
Artificial intelligence Engineering design |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-07716-X
9786611077167 0-08-052976-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Concepts in Artificial Intelligence; Copyright Page; Contents; Preface; Overview of Volume 2; Chapter 1. Introduction; 1.1 Artificial intelligence in engineering; 1.2 Strong AI, weak AI and cognitive science; 7.3 Why build intelligence into machines?; 1.4 How much intelligence can be built into machines?; 1.5 What is artificial intelligence?; 1.6 How is AI applied to engineering in practice?; 1.7 The principles behind the applications; Chapter 2. Pattern recognition; 2.1 Introduction; 2.2 Theoretical foundations; 2.3 Relational patterns and graph matching
2.4 Hierarchical structure in pattern recognition 2.5 Data transformation in pattern recognition; 2.6 Pattern recognition using multidimensional data; 2.7 Multiple classifications and fuzzy sets; 2.8 Errors: non-recognition versus misclassification; 2.9 Rigorous procedures for training pattern recognizers; 2.10 Conclusion; Chapter 3. Search; 3.1 Introduction; 3.2 Tree search; 3.3 Calculus-based search; 3.4 Probabilistic search; 3.5 Conclusion; Chapter 4. Neural networks; 4.1 Introduction; 4.2 The artificial neural unit; 4.3 Pattern classification; 4.4 Feed forward networks 4.5 Learning in neural networks 4.6 Feedback networks; 4.7 Uses of the multi-layer perception; 4.8 Conclusion; Chapter 5. Scheduling; 5.1 Introduction; 5.2 Representation in scheduling; 5.3 Graphs and networks for representing scheduling problems; 5.4 Shortest paths; 5.5 Critical path analysis; 5.6 Critical path activity scheduling; 5.7 The 'travelling salesman problem'; 5.8 Intelligent scheduling; 5.9 Conclusion; Chapter 6. Reasoning; 6.1 introduction; 6.2 Reasoning with certainty; 6.3 Reasoning with uncertainty; 6.4 Conclusion; Chapter 7. Rule-based systems 7.1 Knowledge-based, rule-based and expert systems 7.2 Implementation; 7.3 Confidence levels and fuzzy rules; 7.4 Programming language and rule-based system shells; 7.5 Conclusion; Chapter 8. Learning; 8.1 Introduction; 8.2 Learning by memory; 8.3 Learning by updating parameters; 8.4 learning during execution using Bayesian updating; 8.5 learning from examples; 8.6 learning by analogy; 8.7 Learning by discovery; 8.8 Conclusion; Chapter 9. Intelligent control; 9.1 Introduction; 9.2 The broom-balancer; 9.3 Classical solution; 9.4 Neural network solution; 9.5 Genetic algorithms; 9.6 Fuzzy rules 9.7 Hierarchical control of complex systems 9.8 Conclusion: principles for intelligent control design; Chapter 10. Computer vision; 10.1 Introduction; 10.2 Abstracting information from digital images; 10.3 The nature of digital images; 10.4 Computer vision versus computer graphics; 10.5 Object recognition and measurement; 10.6 A summary of the basic techniques in computer vision; 10.7 A hierarchical architecture for computer vision; 10.8 Conclusion: computer vision in intelligent machines; Chapter 11. Integration; 11.1 An introduction to blackboard systems 11.2 The blackboard system as a development environment |
| Record Nr. | UNINA-9910450552703321 |
Johnson Jeffrey
|
||
| Boston ; ; Oxford, : Butterworth-Heinemann in association with the Open University, 1995 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Designing intelligent machines . Volume 2 Concepts in artificial intelligence [[electronic resource] /] / by Jeffrey Johnson and Philip Picton
| Designing intelligent machines . Volume 2 Concepts in artificial intelligence [[electronic resource] /] / by Jeffrey Johnson and Philip Picton |
| Autore | Johnson Jeffrey |
| Pubbl/distr/stampa | Boston ; ; Oxford, : Butterworth-Heinemann in association with the Open University, 1995 |
| Descrizione fisica | 1 online resource (393 p.) |
| Disciplina |
621
629.89 |
| Altri autori (Persone) | PictonPhilip |
| Soggetto topico |
Mechatronics - Study and teaching
Artificial intelligence Engineering design |
| ISBN |
1-281-07716-X
9786611077167 0-08-052976-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Concepts in Artificial Intelligence; Copyright Page; Contents; Preface; Overview of Volume 2; Chapter 1. Introduction; 1.1 Artificial intelligence in engineering; 1.2 Strong AI, weak AI and cognitive science; 7.3 Why build intelligence into machines?; 1.4 How much intelligence can be built into machines?; 1.5 What is artificial intelligence?; 1.6 How is AI applied to engineering in practice?; 1.7 The principles behind the applications; Chapter 2. Pattern recognition; 2.1 Introduction; 2.2 Theoretical foundations; 2.3 Relational patterns and graph matching
2.4 Hierarchical structure in pattern recognition 2.5 Data transformation in pattern recognition; 2.6 Pattern recognition using multidimensional data; 2.7 Multiple classifications and fuzzy sets; 2.8 Errors: non-recognition versus misclassification; 2.9 Rigorous procedures for training pattern recognizers; 2.10 Conclusion; Chapter 3. Search; 3.1 Introduction; 3.2 Tree search; 3.3 Calculus-based search; 3.4 Probabilistic search; 3.5 Conclusion; Chapter 4. Neural networks; 4.1 Introduction; 4.2 The artificial neural unit; 4.3 Pattern classification; 4.4 Feed forward networks 4.5 Learning in neural networks 4.6 Feedback networks; 4.7 Uses of the multi-layer perception; 4.8 Conclusion; Chapter 5. Scheduling; 5.1 Introduction; 5.2 Representation in scheduling; 5.3 Graphs and networks for representing scheduling problems; 5.4 Shortest paths; 5.5 Critical path analysis; 5.6 Critical path activity scheduling; 5.7 The 'travelling salesman problem'; 5.8 Intelligent scheduling; 5.9 Conclusion; Chapter 6. Reasoning; 6.1 introduction; 6.2 Reasoning with certainty; 6.3 Reasoning with uncertainty; 6.4 Conclusion; Chapter 7. Rule-based systems 7.1 Knowledge-based, rule-based and expert systems 7.2 Implementation; 7.3 Confidence levels and fuzzy rules; 7.4 Programming language and rule-based system shells; 7.5 Conclusion; Chapter 8. Learning; 8.1 Introduction; 8.2 Learning by memory; 8.3 Learning by updating parameters; 8.4 learning during execution using Bayesian updating; 8.5 learning from examples; 8.6 learning by analogy; 8.7 Learning by discovery; 8.8 Conclusion; Chapter 9. Intelligent control; 9.1 Introduction; 9.2 The broom-balancer; 9.3 Classical solution; 9.4 Neural network solution; 9.5 Genetic algorithms; 9.6 Fuzzy rules 9.7 Hierarchical control of complex systems 9.8 Conclusion: principles for intelligent control design; Chapter 10. Computer vision; 10.1 Introduction; 10.2 Abstracting information from digital images; 10.3 The nature of digital images; 10.4 Computer vision versus computer graphics; 10.5 Object recognition and measurement; 10.6 A summary of the basic techniques in computer vision; 10.7 A hierarchical architecture for computer vision; 10.8 Conclusion: computer vision in intelligent machines; Chapter 11. Integration; 11.1 An introduction to blackboard systems 11.2 The blackboard system as a development environment |
| Record Nr. | UNINA-9910783135903321 |
|
Johnson Jeffrey
|
||
| Boston ; ; Oxford, : Butterworth-Heinemann in association with the Open University, 1995 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Designing intelligent machines . Volume 2 Concepts in artificial intelligence / / by Jeffrey Johnson and Philip Picton
| Designing intelligent machines . Volume 2 Concepts in artificial intelligence / / by Jeffrey Johnson and Philip Picton |
| Autore | Johnson Jeffrey |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Boston ; ; Oxford, : Butterworth-Heinemann in association with the Open University, 1995 |
| Descrizione fisica | 1 online resource (393 p.) |
| Disciplina |
621
629.89 |
| Altri autori (Persone) | PictonPhilip |
| Soggetto topico |
Mechatronics - Study and teaching
Artificial intelligence Engineering design |
| ISBN |
1-281-07716-X
9786611077167 0-08-052976-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Concepts in Artificial Intelligence; Copyright Page; Contents; Preface; Overview of Volume 2; Chapter 1. Introduction; 1.1 Artificial intelligence in engineering; 1.2 Strong AI, weak AI and cognitive science; 7.3 Why build intelligence into machines?; 1.4 How much intelligence can be built into machines?; 1.5 What is artificial intelligence?; 1.6 How is AI applied to engineering in practice?; 1.7 The principles behind the applications; Chapter 2. Pattern recognition; 2.1 Introduction; 2.2 Theoretical foundations; 2.3 Relational patterns and graph matching
2.4 Hierarchical structure in pattern recognition 2.5 Data transformation in pattern recognition; 2.6 Pattern recognition using multidimensional data; 2.7 Multiple classifications and fuzzy sets; 2.8 Errors: non-recognition versus misclassification; 2.9 Rigorous procedures for training pattern recognizers; 2.10 Conclusion; Chapter 3. Search; 3.1 Introduction; 3.2 Tree search; 3.3 Calculus-based search; 3.4 Probabilistic search; 3.5 Conclusion; Chapter 4. Neural networks; 4.1 Introduction; 4.2 The artificial neural unit; 4.3 Pattern classification; 4.4 Feed forward networks 4.5 Learning in neural networks 4.6 Feedback networks; 4.7 Uses of the multi-layer perception; 4.8 Conclusion; Chapter 5. Scheduling; 5.1 Introduction; 5.2 Representation in scheduling; 5.3 Graphs and networks for representing scheduling problems; 5.4 Shortest paths; 5.5 Critical path analysis; 5.6 Critical path activity scheduling; 5.7 The 'travelling salesman problem'; 5.8 Intelligent scheduling; 5.9 Conclusion; Chapter 6. Reasoning; 6.1 introduction; 6.2 Reasoning with certainty; 6.3 Reasoning with uncertainty; 6.4 Conclusion; Chapter 7. Rule-based systems 7.1 Knowledge-based, rule-based and expert systems 7.2 Implementation; 7.3 Confidence levels and fuzzy rules; 7.4 Programming language and rule-based system shells; 7.5 Conclusion; Chapter 8. Learning; 8.1 Introduction; 8.2 Learning by memory; 8.3 Learning by updating parameters; 8.4 learning during execution using Bayesian updating; 8.5 learning from examples; 8.6 learning by analogy; 8.7 Learning by discovery; 8.8 Conclusion; Chapter 9. Intelligent control; 9.1 Introduction; 9.2 The broom-balancer; 9.3 Classical solution; 9.4 Neural network solution; 9.5 Genetic algorithms; 9.6 Fuzzy rules 9.7 Hierarchical control of complex systems 9.8 Conclusion: principles for intelligent control design; Chapter 10. Computer vision; 10.1 Introduction; 10.2 Abstracting information from digital images; 10.3 The nature of digital images; 10.4 Computer vision versus computer graphics; 10.5 Object recognition and measurement; 10.6 A summary of the basic techniques in computer vision; 10.7 A hierarchical architecture for computer vision; 10.8 Conclusion: computer vision in intelligent machines; Chapter 11. Integration; 11.1 An introduction to blackboard systems 11.2 The blackboard system as a development environment |
| Record Nr. | UNINA-9910826593703321 |
|
Johnson Jeffrey
|
||
| Boston ; ; Oxford, : Butterworth-Heinemann in association with the Open University, 1995 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
