Название: Artificial Intelligence: Principles and Practice Автор: George F. Luger Издательство: Springer Год: 2025 Страниц: 639 Язык: английский Формат: pdf (true) Размер: 30.2 MB
This book provides a complete introduction to Artificial Intelligence (AI), covering foundational computational technologies, mathematical principles, philosophical considerations, and engineering disciplines essential for understanding AI. Artificial Intelligence: Principles and Practice emphasizes the interdisciplinary nature of AI, integrating insights from psychology, mathematics, neuroscience, and more. The book addresses limitations, ethical issues, and the future promise of AI, emphasizing the importance of ethical considerations in integrating AI into modern society. With a modular design, it offers flexibility for instructors and students to focus on specific components of AI, while also providing a holistic view of the field.
This book offers a comprehensive introduction to the exciting and too often mysterious discipline of Artificial Intelligence. As an introduction to AI, it covers the foundational computational technologies that have supported work in AI since its inception over 70 years ago. In Part I, it covers the mathematical, philosophical, and engineering disciplines that make Artificial Intelligence possible. AI is not a standalone discipline but rather integrates and expands the many insights of the psychologists, mathematicians, neuroscientists, and others that are part of its current research and practice. The final chapters, Part VIII, focus on the limitations, ethical issues, and future promise of AI.
I 1. The Pre-History of Artificial Intelligence 2. Computing, Representations, and Definitions of Artificial Intelligence II 3. The State Space, Finite State Machines, and Artificial Life 4. Searching the State Space 5. Heuristic Search 6. Heuristics: 2-Person Games and Theoretical Constraints III 7. Introduction to the Propositional and Predicate Calculi 8. The Predicate Calculus and Unification 9. Resolution: Reasoning with the Propositional and Predicate Calculi IV 10. The Production System Representation and Search Engine 11. Advanced Applications of Symbol-Based AI: Planning and Learning 12. Uncertain Reasoning: Symbol Based V 13. Introduction to Association-Based Knowledge Representations 14. Association-Based Representations: Frames, Conceptual Graphs, WordNet, and FrameNet VI 15. An Introduction to Neural Networks 16. The Delta Rule, Backpropagation, and Matrix Representations 17. Deep Learning: Introduction and Representations 18. Building Language Models and Transformers 19. Alternative Network Architectures: Prototypes and Classifiers 20. Alternative Network Architectures: Attractor Networks and Memories VII 21. Counting, the Foundation for Probabilities 22. Bayes’ Theorem 23. Bayesian Belief Networks and Observable Markov Models 24. Hidden Markov and Alternative Probabilistic Models VIII 25. Artificial Intelligence: User’s Ethical Issues 26. AI Ethical Issues: From a Social Perspective 27. AI: Philosophical Perspectives, Current Limitations, and Future Promise
Скачать Artificial Intelligence: Principles and Practice