Artificial intelligence :
Neapolitan, Richard E.
Artificial intelligence : with an introduction to machine learning / Richard E. Neapolitan, Xia Jiang. - Second edition. - xiii, 466 pages : illustrations ; 27 cm. - Chapman & Hall/CRC artificial intelligence and robotics series .
"A Chapman & Hall book."
Includes bibliographical references (pages 437-457) and index.
1. Introduction to Artificial Intelligence --
Part 1. Logical Intelligence --
2. Propositional Logic --
3. First-Order Logic --
4. Certain Knowledge Representation --
5. Learning Deterministic Models --
Part 2. Probabilistic Intelligence --
6. Probability --
7. Uncertain Knowledge Representation --
8. Advanced Properties of Bayesian Network --
9. Decision Analysis --
10. Learning Probabilistic Model Parameters --
11. Learning Probabilistic Model Structure --
12. Unsupervised Learning and Reinforcement Learning --
Part 3. Emergent Intelligence --
13. Evolutionary Computation --
14. Swarm Intelligence --
Part 4: Neural Intelligence --
15. Neural Networks and Deep Learning --
Part 5. Language Understanding --
16. Natural Language Understanding.
The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods.
The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding.
Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more.
9780367571641 9781138502383
Artificial intelligence
006.3
Artificial intelligence : with an introduction to machine learning / Richard E. Neapolitan, Xia Jiang. - Second edition. - xiii, 466 pages : illustrations ; 27 cm. - Chapman & Hall/CRC artificial intelligence and robotics series .
"A Chapman & Hall book."
Includes bibliographical references (pages 437-457) and index.
1. Introduction to Artificial Intelligence --
Part 1. Logical Intelligence --
2. Propositional Logic --
3. First-Order Logic --
4. Certain Knowledge Representation --
5. Learning Deterministic Models --
Part 2. Probabilistic Intelligence --
6. Probability --
7. Uncertain Knowledge Representation --
8. Advanced Properties of Bayesian Network --
9. Decision Analysis --
10. Learning Probabilistic Model Parameters --
11. Learning Probabilistic Model Structure --
12. Unsupervised Learning and Reinforcement Learning --
Part 3. Emergent Intelligence --
13. Evolutionary Computation --
14. Swarm Intelligence --
Part 4: Neural Intelligence --
15. Neural Networks and Deep Learning --
Part 5. Language Understanding --
16. Natural Language Understanding.
The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods.
The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding.
Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more.
9780367571641 9781138502383
Artificial intelligence
006.3