Artificial Intelligence: A Guide to Intelligent Systems

<div class="c-header-numbers-with-list_container"> <ol> <li><strong>Introduction to Intelligent Systems</strong> <ul> <li>1.1 Intelligent Machines, or What Machines Can Do</li> <li>1.2 The History of Artificial Intelligence, or From the ‘Dark Ages’ to Knowledge-based Systems</li> <li>1.3 Generative AI</li> <li>1.4 Summary</li> <li>Questions for Review</li> <li>References</li> </ul> </li> <li><strong>Expert Systems</strong> <ul> <li>2.1 Introduction, or Knowledge Representation Using Rules</li> <li>2.2 The Main Players in the Expert System Development Team</li> <li>2.3 Structure of a Rule-based Expert System</li> <li>2.4 Fundamental characteristics of an expert system</li> <li>2.5 Forward Chaining and Backward Chaining Inference Techniques</li> <li>2.6 MEDIA ADVISOR: A Demonstration Rule-based Expert System</li> <li>2.7 Conflict Resolution</li> <li>2.8 Uncertainty Management in Rule-based Expert Systems</li> <li>2.9 Advantages and Disadvantages of Rule-based Expert systems</li> <li>2.10 Summary</li> <li>Questions for Review</li> <li>References</li> </ul> </li> <li><strong>Fuzzy Systems</strong> <ul> <li>3.1 Introduction, or What Is Fuzzy Thinking?</li> <li>3.2 Fuzzy Sets</li> <li>3.3 Linguistic Variables and Hedges</li> <li>3.4 Operations of Fuzzy Sets</li> <li>3.6 Fuzzy Inference</li> <li>3.7 Building a Fuzzy Expert System</li> <li>3.8 Summary</li> <li>Questions for Review</li> <li>References</li> </ul> </li> <li><strong>Frame-based Systems and Semantic Networks</strong> <ul> <li>4.1 Introduction, or What Is a Frame?</li> <li>4.2 Frames as a Knowledge Representation Technique</li> <li>4.3 Inheritance in Frame-based Systems</li> <li>4.4 Methods and Demons</li> <li>4.5 Interaction of Frames and Rules</li> <li>4.6 Buy Smart: A Frame-based Expert System</li> <li>4.7 The Web of Data</li> <li>4.8 RDF – Resource Description Framework and RDF Triples</li> <li>4.9 Turtle, RDF Schema and OWL</li> <li>4.10 Querying the Semantic Web with SPARQL</li> <li>4.11 Summary</li> <li>Questions for Review</li> <li>References</li> </ul> </li> <li><strong>Artificial Neural Networks</strong> <ul> <li>5.1 Introduction, or How the Brain Works</li> <li>5.2 The Neuron as a Simple Computing Element</li> <li>5.3 The Perceptron</li> <li>5.4 Multilayer Neural Networks</li> <li>5.5 Accelerated Learning in Multilayer Neural Networks</li> <li>5.6 The Hopfield Network</li> <li>5.7 Bidirectional Associative Memory</li> <li>5.8 Self-organising Neural Networks</li> <li>5.9 Reinforcement Learning</li> <li>5.10 Summary</li> <li>Questions for Review</li> <li>References</li> </ul> </li> <li><strong>Deep Learning and Convolutional Neural Networks</strong> <ul> <li>6.1 Introduction, or How “Deep” Is a Deep Neural Network?</li> <li>6.2 Image Recognition or How Machines See the World</li> <li>6.3 Convolution in Machine Learning</li> <li>6.4 Activation Functions in Deep Neural Networks</li> <li>6.5 Convolutional Neural Networks</li> <li>6.6 Back-propagation Learning in Convolutional Networks</li> <li>6.7 Batch Normalisation</li> <li>6.8 Summary</li> <li>Questions for Review</li> <li>References</li> </ul> </li> <li><strong>Evolutionary Computation</strong> <ul> <li>7.1 Introduction, or Can Evolution Be Intelligent?</li> <li>7.2 Simulation of Natural Evolution</li> <li>7.3 Genetic Algorithms</li> <li>7.4 Why Genetic Algorithms Work</li> <li>7.5 Maintenance Scheduling with Genetic Algorithms</li> <li>7.6 Genetic Programming</li> <li>7.7 Evolution Strategies</li> <li>7.8 Ant Colony Optimisation</li> <li>7.9 Particle Swarm Optimisation</li> <li>7.10 Summary</li> <li>Questions for Review</li> <li>References</li> </ul> </li> <li><strong>Hybrid Intelligent Systems</strong> <ul> <li>8.1 Introduction, or How to Combine German Mechanics with Italian Love</li> <li>8.2 Neural Expert Systems</li> <li>8.3 Neuro-Fuzzy Systems</li> <li>8.4 ANFIS: Adaptive Neuro-Fuzzy Inference System</li> <li>8.5 Evolutionary Neural Networks</li> <li>8.6 Fuzzy Evolutionary Systems</li> <li>8.7 Summary</li> <li>Questions for Review</li> <li>References</li> </ul> </li> <li><strong>Knowledge Engineering</strong> <ul> <li>9.1 Introduction, or What Is Knowledge Engineering?</li> <li>9.2 Will an Expert System Work for My Problem?</li> <li>9.3 Will a Fuzzy Expert System Work for My Problem?</li> <li>9.4 Will a Neural Network Work for My Problem?</li> <li>9.5 Will a Deep Neural Network Work for My Problem?</li> <li>9.6 Will Genetic Algorithms Work for My Problem?</li> <li>9.7 Will Particle Swarm Optimisation Work for My Problem?</li> <li>9.8 Will a Hybrid Intelligent System Work for My Problem?</li> <li>9.9 Summary</li> <li>Questions for Review</li> <li>References</li> </ul> </li> <li><strong>Data Mining and Knowledge Discovery</strong> <ul> <li>10.1 Introduction, or What Is Data Mining?</li> <li>10.2 Statistical Methods and Data Visualisation</li> <li>10.3 Principal Components Analysis</li> <li>10.4 Relational Databases and Database Queries</li> <li>10.5 The Data Warehouse and Multidimensional Data Analysis</li> <li>10.6 Decision Trees</li> <li>10.7 Association Rules and Market Basket Analysis</li> <li>10.8 Summary</li> <li>Questions for Review</li> <li>References</li> </ul> </li> </ol> <ul> <li>Glossary</li> <li>Index</li> </ul> </div>