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Introduction to artificial intelligence / Wolfgang Ertel..

By: Material type: TextTextSeries: Undergraduate topics in computer sciencePublication details: London ; New York : Springer, c2011.Description: xi, 316 p. : ill. (some col.) ; 24 cmISBN:
  • 9780857292988
  • 0857292986
Subject(s): DDC classification:
  • 006.3   22
Contents:
1. Introduction -- 2 Propositional Logic -- 3 First-order Predicate Logic -- 4 Limitations of Logic -- 5 Logic Programming with PROLOG -- 6 Search, Games and Problem Solving -- 7 Reasoning with Uncertainty -- 8 Machine Learning and Data Mining -- 9 Neural Networks -- 10 Reinforcement Learning -- 11 Solutions for the Exercises.
Summary: 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.
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Item type Current library Call number Copy number Status Date due Barcode
Books Books Main library General Stacks 006.3 / ER.I 2011 (Browse shelf(Opens below)) 1 Available 011664

Includes bibliographical references (p. 305-310) and index.

1. Introduction -- 2 Propositional Logic -- 3 First-order Predicate Logic -- 4 Limitations of Logic -- 5 Logic Programming with PROLOG -- 6 Search, Games and Problem Solving -- 7 Reasoning with Uncertainty -- 8 Machine Learning and Data Mining -- 9 Neural Networks -- 10 Reinforcement Learning -- 11 Solutions for the Exercises.

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.

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