INTRODUCTION TO ARTIFICIAL INTELLIGENCE
PHI Learning Pvt. Ltd., 18. jul. 2014 - 440 sider
This comprehensive text acquaints the readers with the important aspects of artificial intelligence (AI) and intelligent systems and guides them towards a better understanding of the subject. The text begins with a brief introduction to artificial intelligence, including application areas, its history and future, and programming. It then deals with symbolic logic, knowledge acquisition, representation and reasoning. The text also lucidly explains AI technologies such as computer vision, natural language processing, pattern recognition and speech recognition. Topics such as expert systems, neural networks, constraint programming and case-based reasoning are also discussed in the book. In the Second Edition, the contents and presentation have been improved thoroughly and in addition six new chapters providing a simulating and inspiring synthesis of new artificial intelligence and an appendix on AI tools have been introduced. The treatment throughout the book is primarily tailored to the curriculum needs of B.E./B.Tech. students in Computer Science and Engineering, B.Sc. (Hons.) and M.Sc. students in Computer Science, and MCA students. The book is also useful for computer professionals interested in exploring the field of artificial intelligence. Key Features • Exposes the readers to real-world applications of AI. • Concepts are duly supported by examples and cases. • Provides appendices on PROLOG, LISP and AI Tools. • Incorporates most recommendations of the Curriculum Committee on Computer Science/Engineering for AI and Intelligent Systems. • Exercises provided will help readers apply what they have learned.
Hva folk mener - Skriv en omtale
Vi har ikke funnet noen omtaler på noen av de vanlige stedene.
CHAPTER 14 Soft Computing
CHAPTER 15 Robotics
CHAPTER 16 Machine Learning
CHAPTER 17 Intelligent Systems
CHAPTER 18 Applications of Artificial Intelligence
APPENDIX A Projects
APPENDIX B PROLOG
APPENDIX C LISP
actions agents applications approach architecture artificial intelligence atoms backward chaining behaviour called case-based reasoning classification clause clustering complex components computer concepts constraint programming constraints control data database defined design developed different domain engineering environment evaluation example expert system facts features Figure following form formula forward chaining frame function fuzzy logic fuzzy set genetic algorithms given goal grammar graph heuristic human hypothesis image implemented inference information input intelligent systems interaction knowledge base knowledge representation layer level LISP list machine learning match methods model natural language need neural network neuron node number objects ontology operators optimal output parsing path pattern recognition performance planning possible predicate problem problem-solving procedure process produce PROLOG propositional provide queue represent required research retrieved robot rule-based rules s-expression script search semantic semantic network sentence software solution solve specific strategy structure subset symbolic task techniques test theorem theory type unsupervised learning user value variables