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Artificial Intelligence Basics: A Self-Teaching Introduction [Pehme köide]

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  • Formaat: Paperback / softback, 203 pages, kaal: 345 g
  • Ilmumisaeg: 18-Mar-2020
  • Kirjastus: Mercury Learning & Information
  • ISBN-10: 1683925165
  • ISBN-13: 9781683925163
Teised raamatud teemal:
Artificial Intelligence Basics: A Self-Teaching IntroductionSuurem pilt
  • Formaat: Paperback / softback, 203 pages, kaal: 345 g
  • Ilmumisaeg: 18-Mar-2020
  • Kirjastus: Mercury Learning & Information
  • ISBN-10: 1683925165
  • ISBN-13: 9781683925163
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781683925163.html
Märksõnad:
"Designed as a self-teaching introduction to the fundamental concepts of artificial intelligence, the book begins with its history, the Turing test, and early applications. Later chapters cover the basics of searching, game playing, and knowledge representation. Expert systems and machine learning are covered in detail, followed by separate programming chapters on Prolog and Python. The concluding chapter on artificial intelligence machines and robotics is comprehensive with numerous modern applications.

In a self-teaching introduction to the fundamental concepts of artificial intelligence, Gupta and Mangla begin with the history of the field, the Turing test, and early applications. Then they explore the basics of searching, game playing, and knowledge representation, and describe expert systems and machine learning in detail, followed by separate programming chapters on Prolog and Python. Their final chapter surveys applications of artificial intelligence in machines and robotics. Distributed in North America by Stylus Publishing and Distribution. Annotation ©2020 Ringgold, Inc., Portland, OR (protoview.com)

Designed as a self-teachingintroduction to the fundamental concepts of artificial intelligence, the book beginswith its history, the Turing test, and early applications. Later chapters coverthe basics of searching, game playing, and knowledge representation. Expertsystems and machine learning are covered in detail, followed by separateprogramming chapters on Prolog and Python. The concluding chapter on artificialintelligence machines and robotics is comprehensive with numerous modernapplications.

Features:
  • Covers an introduction toconcepts related to AI, including searching processes, knowledge representation,machine learning, expert systems, programming, and robotics
  • Includes separate chapterson Prolog and Python to introduce basic programming techniques in AI
Acknowledgments ix
1 Artificial Intelligence (Ai)
1(12)
1.1 Computerized Reasoning
1(1)
1.2 Turing Test
2(1)
1.3 What is Intelligence?
3(1)
1.4 Artificial Intelligence
4(1)
1.5 Goals of Artificial Intelligence
4(1)
1.6 History of Artificial Intelligence
5(2)
1.7 Advantages of Artificial Intelligence
7(1)
1.8 Application Areas of Artificial Intelligence
7(3)
1.9 Components of Artificial Intelligence
10(3)
2 Problem Representation
13(12)
2.1 Introduction
13(1)
2.2 Problem Characteristics
13(1)
2.3 Problem Representation in AI
14(4)
2.4 Production System
18(4)
2.5 Conflict Resolution
22(3)
3 The Search Process
25(18)
3.1 Search Process
25(1)
3.2 Strategies for Search
26(1)
3.3 Search Techniques
26(17)
4 Game Playing
43(10)
4.1 Game Playing
43(1)
4.2 Game Tree
44(1)
4.3 Components of a Game Playing Program
44(1)
4.4 Game Playing Strategies
45(5)
4.5 Problems in Computer Game Playing Programs
50(3)
5 Knowledge Representation
53(18)
5.1 Introduction
53(1)
5.2 Definition of Knowledge
53(3)
5.3 Importance of Knowledge
56(1)
5.4 Knowledge-based Systems
56(1)
5.5 Differences between Knowledge-based Systems and Database Systems
56(1)
5.6 Knowledge Representation Scheme
57(14)
6 Expert Systems
71(24)
6.1 Introduction
71(1)
6.2 Definition of an Expert System
71(1)
6.3 Characteristics of an Expert System
72(1)
6.4 Architectures of Expert Systems
72(12)
6.5 Expert System Life Cycle
84(2)
6.6 Knowledge Engineering Process
86(1)
6.7 Knowledge Acquisition
87(1)
6.8 Difficulties in Knowledge Acquisition
87(1)
6.9 Knowledge Acquisition Strategies
88(1)
6.10 Advantages of Expert Systems
89(1)
6.11 Limitations of Expert Systems
90(1)
6.12 Examples of Expert Systems
91(4)
7 Learning
95(10)
7.1 Learning
95(1)
7.2 General Model for Machine Learning Systems
95(2)
7.3 Characteristics of Machine Learning
97(1)
7.4 Types of Learning
97(6)
7.5 Advantages of Machine Learning
103(1)
7.6 Disadvantages of Machine Learning
103(2)
8 Prolog
105(16)
8.1 Preliminaries of Prolog
105(1)
8.2 Milestones in Prolog Language Development
106(1)
8.3 What is a Horn Clause?
106(1)
8.4 Robinsons Resolution Rule
107(1)
8.5 Parts of a Prolog Program
107(1)
8.6 Queries to a Database
108(1)
8.7 How does Prolog Solve a Query?
109(1)
8.8 Compound Queries
109(1)
8.9 The Variable
109(1)
8.10 Recursion in Prolog
110(1)
8.11 Data Structures in Prolog
111(1)
8.12 Head and Tail of a List
111(1)
8.13 Print all the Members of the List
112(1)
8.14 Print the List in Reverse Order
112(1)
8.15 Appending a List
113(1)
8.16 Find Whether the Given Item is a Member of the List
113(1)
8.17 Finding the Length of the List
113(1)
8.18 Controlling Execution in Prolog
113(4)
8.19 About Turbo Prolog
117(4)
9 Python
121(18)
9.1 Languages Used for Building AI
121(1)
9.2 Why Do People Choose Python?
121(1)
9.3 Build AI Using Python
122(2)
9.4 Running Python
124(1)
9.5 Pitfalls
125(1)
9.6 Features of Python
125(7)
9.7 Useful Libraries
132(2)
9.8 Utilities
134(3)
9.9 Testing Code
137(2)
10 Artificial Intelligence Machines And Robotics
139(48)
10.0 Introduction
139(4)
10.1 History: Serving, Emulating, Enhancing, and Replacing Man
143(17)
10.2 Technical Issues
160(10)
10.3 Applications: Robotics in the Twenty-First Century
170(12)
10.4 Summary
182(5)
Review Questions 187(6)
Index 193
Gupta N. : N. Gupta, PhD teaches courses in artificial intelligence and specializes in expert systems.

Mangla R. : R. Mangla is the proprietor of a large manufacturing company using AI machines.