Artificial Intelligence: A Guide to Intelligent Systems

Artificial Intelligence: A Guide to Intelligent Systems


By (author) Michael Negnevitsky

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  • Publisher: Addison Wesley
  • Format: Paperback | 504 pages
  • Dimensions: 154mm x 232mm x 28mm | 780g
  • Publication date: 19 August 2011
  • Publication City/Country: Harlow
  • ISBN 10: 1408225743
  • ISBN 13: 9781408225745
  • Edition: 3, Revised
  • Edition statement: 3rd Revised edition
  • Sales rank: 321,802

Product description

Negnevitsky shows students how to build intelligent systems drawing on techniques from knowledge-based systems, neural networks, fuzzy systems, evolutionary computation and now also intelligent agents. The principles behind these techniques are explained without resorting to complex mathematics, showing how the various techniques are implemented, when they are useful and when they are not. No particular programming language is assumed and the book does not tie itself to any of the software tools available. However, available tools and their uses are described, and program examples are given in Java.The lack of assumed prior knowledge makes this book ideal for any introductory courses in artificial intelligence or intelligent systems design, while the contemporary coverage means more advanced students will benefit by discovering the latest state-of-the-art techniques, particularly in intelligent agents and knowledge discovery.

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Author information

Dr Michael Negnevitsky is a Professor in Electrical Engineering and Computer Science at the University of Tasmania, Australia. The book has developed from his lectures to undergraduates. Educated as an electrical engineer, Dr Negnevitsky's many interests include artificial intelligence and soft computing. His research involves the development and application of intelligent systems in electrical engineering, process control and environmental engineering. He has authored and co-authored over 300 research publications including numerous journal articles, four patents for inventions and two books.

Review quote

"This book covers many areas related to my module. I would be happy to recommend this book to my students. I believe my students would be able to follow this book without any difficulty. Book chapters are very well organised and this will help me to pick and choose the subjects related to this module." Dr Ahmad Lotfi, Nottingham Trent University, UK

Table of contents

 Contents  Preface                                                                                    xiiNew to this edition                                                                            xiiiOverview of the book                                                           xivAcknowledgements                                                                          xvii 1        Introduction to knowledge-based intelligent systems                                1 1.1     Intelligent machines, or what machines can do                            11.2     The history of artificial intelligence, or from the ‘Dark Ages’          to knowledge-based systems                                                       41.3     Summary                                                                         17          Questions for review                                                                   21          References                                                                      22 2        Rule-based expert systems                                                              25 2.1     Introduction, or what is knowledge?                                            252.2     Rules as a knowledge representation technique                        262.3     The main players in the expert system development team                    282.4     Structure of a rule-based expert system                                    302.5     Fundamental characteristics of an expert system                     332.6     Forward chaining and backward chaining inference techniques                                                                       352.7     MEDIA ADVISOR: a demonstration rule-based expert system        412.8     Conflict resolution                                                            472.9     Advantages and disadvantages of rule-based expert systems        502.10   Summary                                                                         51          Questions for review                                                                   53          References                                                                      54 3        Uncertainty management in rule-based expert systems              55 3.1     Introduction, or what is uncertainty?                                           553.2     Basic probability theory                                                               573.3     Bayesian reasoning                                                         613.4     FORECAST: Bayesian accumulation of evidence                     653.5     Bias of the Bayesian method                                                      723.6     Certainty factors theory and evidential reasoning                       743.7     FORECAST: an application of certainty factors                         803.8     Comparison of Bayesian reasoning and certainty factors          823.9     Summary                                                                         83          Questions for review                                                                   85          References                                                                      85 4        Fuzzy expert systems                                                            87 4.1     Introduction, or what is fuzzy thinking?                                       874.2     Fuzzy sets                                                                       894.3     Linguistic variables and hedges                                                  944.4     Operations of fuzzy sets                                                             974.5     Fuzzy rules                                                                    1034.6     Fuzzy inference                                                                         1064.7     Building a fuzzy expert system                                                 1144.8     Summary                                                                       125          Questions for review                                                                 126          References                                                                    127          Bibliography                                                                   127 5        Frame-based expert systems                                                         131 5.1     Introduction, or what is a frame?                                               1315.2     Frames as a knowledge representation technique                   1335.3     Inference in frame-based experts                                             1385.4     Methods and demons                                                                1425.5     Interaction of frames and rules                                                 1465.6     Buy Smart: a frame-based expert system                                1495.7     Summary                                                                       161          Questions for review                                                                 163          References                                                                    163          Bibliography                                                                   164 6        Artificial neural networks                                                                165 6.1     Introduction, or how the brain works                                         1656.2     The neuron as a simple computing element                                        1686.3     The perceptron                                                                          1706.4     Multilayer neural networks                                             1756.5     Accelerated learning in multilayer neural networks                   1856.6     The Hopfield network                                                                 1886.7     Bidirectional associative memories                                                      1966.8     Self-organising neural networks                                                2006.9     Summary                                                                       212          Questions for review                                                                 215          References                                                                    216 7        Evolutionary computation                                                               219 7.1     Introduction, or can evolution be intelligent?                             2197.2     Simulation of natural evolution                                                  2197.3     Genetic algorithms                                                        2227.4     Why genetic algorithms work                                                    2327.5     Case study: maintenance scheduling with genetic algorithms                                                                      2357.6     Evolutionary strategies                                                              2427.7     Genetic programming                                                               2457.8     Summary                                                                       254          Questions for review                                                                 255          References                                                                    256          Bibliography                                                                   257 8        Hybrid intelligent systems                                                               259 8.1     Introduction, or how to combine German mechanics with Italian love                                                                          2598.2     Neural expert systems                                                              2618.3     Neuro-fuzzy systems                                                                2688.4     ANFIS: Adaptive Neuro-Fuzy Inference System                       2778.5     Evolutionary neural networks                                                    2858.6     Fuzzy evolutionary systems                                                     2908.7     Summary                                                                       296          Questions for review                                                                 297          References                                                                    298 9        Knowledge engineering                                                                  301 9.1     Introduction, or what is knowledge engineering?                      3019.2     Will an expert system work for my problem?                           3089.3     Will a fuzzy expert system work for my problem?                    3179.4     Will a neural network work for my problem?                             3239.5     Will genetic algorithms work for my problem?                          9.6     Will a hybrid intelligent system work for my problem?           9.7     Summary                                                                                 Questions for review                                                                           References                                                                     10    Data mining and knowledge discovery                                          10.1   Introduction, or what is data mining?                                        10.2   Statistical methods and data visualisation                                10.3   Principal components analysis                                                 10.4   Relational databases and database queries                                         10.5   The data warehouse and multidimensional data analysis        10.6   Decision trees                                                                           10.7   Association rules and market basket analysis                          10.8   Summary                                                                                 Questions for review                                                                           References                                                                               Glossary                                                                                 Appendix                                                                                Index