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Introduction to Artificial Intelligence (Undergraduate Topics in Computer Science)

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Introduction to Artificial Intelligence (Undergraduate Topics in Computer Science) Cover

 

Synopses & Reviews

Publisher Comments:

The ultimate aim of artificial intelligence (A.I.) is to understand intelligence and to build intelligent software and robots that come close to the performance of humans. On their way towards this goal, A.I. researchers have developed a number of quite different subdisciplines. This concise and accessible Introduction to Artificial Intelligence supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The textbook presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning. Topics and features: Presents an application-focused and hands-on approach to learning the subjectProvides study exercises of varying degrees of difficulty at the end of each chapter, with solutions given at the end of the bookSupports the text with highlighted examples, definitions, theorems, and illustrative cartoonsIncludes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learningContains an extensive bibliography for deeper reading on further topicsSupplies additional teaching resources, including lecture slides and training data for learning algorithms, at the website http://www.hs-weingarten.de/~ertel/aibookStudents of computer science and other technical natural sciences will find this easy-to-read textbook excellent for self-study, a high-school level of knowledge of mathematics being the only prerequisite to understanding the material. With its extensive tools and bibliography, it is an ideal, quick resource on A.I. Dr. Wolfgang Ertel is a professor at the Collaborative Center for Applied Research on Service Robotics at the Ravensburg-Weingarten University of Applied Sciences, Germany.

Synopsis:

This accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. It provides study exercises at the end of each chapter, plus examples, definitions, theorems, and illustrations.

Synopsis:

This concise and accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The book presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning. Topics and features: presents an application-focused and hands-on approach to learning the subject; provides study exercises of varying degrees of difficulty at the end of each chapter, with solutions given at the end of the book; supports the text with highlighted examples, definitions, and theorems; includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; contains an extensive bibliography for deeper reading on further topics; supplies additional teaching resources, including lecture slides and training data for learning algorithms, at an associated website.

About the Author

Dr. Wolfgang Ertel is a professor at the Collaborative Center for Applied Research on Service Robotics at the Ravensburg-Weingarten University of Applied Sciences, Germany.

Table of Contents

Introduction Propositional Logic First-order Predicate Logic Limitations of Logic Logic Programming with PROLOG Search, Games and Problem Solving Reasoning with Uncertainty Machine Learning and Data Mining Neural Networks Reinforcement Learning Solutions for the Exercises

Product Details

ISBN:
9780857292988
Author:
Ertel, Wolfgang
Publisher:
Springer
Author:
Black, Nathanael T.
Subject:
Artificial Intelligence
Subject:
Artificial Intelligence (incl. Robotics)
Subject:
Computers-Reference - General
Copyright:
Edition Description:
2011
Series:
Undergraduate Topics in Computer Science
Publication Date:
20110429
Binding:
TRADE PAPER
Language:
English
Pages:
328
Dimensions:
235 x 155 mm

Related Subjects

Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
Health and Self-Help » Health and Medicine » Medical Specialties

Introduction to Artificial Intelligence (Undergraduate Topics in Computer Science) New Trade Paper
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Product details 328 pages Springer - English 9780857292988 Reviews:
"Synopsis" by , This accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. It provides study exercises at the end of each chapter, plus examples, definitions, theorems, and illustrations.
"Synopsis" by , This concise and accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The book presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning. Topics and features: presents an application-focused and hands-on approach to learning the subject; provides study exercises of varying degrees of difficulty at the end of each chapter, with solutions given at the end of the book; supports the text with highlighted examples, definitions, and theorems; includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; contains an extensive bibliography for deeper reading on further topics; supplies additional teaching resources, including lecture slides and training data for learning algorithms, at an associated website.
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