The thoroughly updated fourth edition features new coverage of deep learning algorithms. Using clear and concise language, it explains the principles of artificial intelligence (AI) and its practical applications. It gives engineers and scientists a solid grounding in AI so that its they can implement systems in their own domain of interest.
The thoroughly updated fourth edition features new coverage of deep learning algorithms. Using clear and concise language, it explains the principles of artificial intelligence (AI) and its practical applications. It gives engineers and scientists a solid grounding in AI so that its they can implement systems in their own domain of interest.
Dr. Adrian Hopgood is Professor of Intelligent Systems and Director of Future & Emerging Technologies at the University of Portsmouth in the UK. He is a Chartered Engineer, Chartered IT Professional, Fellow of the BCS (British Computer Society, the Chartered Institute for IT), and a committee member for the BCS Specialist Group on Artificial Intelligence. He earned his BSc from the University of Bristol, PhD from the University of Oxford, and MBA from the Open University. After completing his PhD, he joined the AI team of Systems Designers PLC. That experience set the direction of his career toward the investigation of intelligent systems and their practical applications. After leaving Systems Designers, he spent 14 years at the Open University and remains attached as a visiting professor. During that period, he also spent two years at Telstra Research Laboratories in Australia, investigating the role of intelligent systems in telecommunications. He has subsequently worked for Nottingham Trent University, De Montfort University, Sheffield Hallam University, and the University of Liège, before joining the University of Portsmouth. Despite assuming several senior management positions during his career, he has never lost his passion for intelligent systems. He has supervised 20 PhD projects to completion and published more than 100 research articles. His website is adrianhopgood.com.
Inhaltsangabe
1. Introduction 2. Rule-Based Systems 3. Handling Uncertainty: Probability and Fuzzy Logic 4. Agents Objects and Frames 5. Symbolic Learning 6. Single-Candidate Optimization Algorithms 7. Genetic Algorithms for Optimization 8. Shallow Neural Networks 9. Deep Neural Networks 10. Hybrid Systems 11. AI Programming Languages and Tools 12. Systems for Interpretation and Diagnosis 13. Systems for Design and Selection 14. Systems for Planning 15. Systems for Control 16. The Future of Intelligent Systems References.
1. Introduction 2. Rule-Based Systems 3. Handling Uncertainty: Probability and Fuzzy Logic 4. Agents Objects and Frames 5. Symbolic Learning 6. Single-Candidate Optimization Algorithms 7. Genetic Algorithms for Optimization 8. Shallow Neural Networks 9. Deep Neural Networks 10. Hybrid Systems 11. AI Programming Languages and Tools 12. Systems for Interpretation and Diagnosis 13. Systems for Design and Selection 14. Systems for Planning 15. Systems for Control 16. The Future of Intelligent Systems References.
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