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Introduction to Artificial Intelligence / Wolfgang Ertel ; translated by Nathanael Black ; with illustrations by Florian Mast.

By: Contributor(s): Material type: TextTextSeries: Undergraduate topics in computer sciencePublisher: Cham, Switzerland : Springer, 2017Edition: Second editionDescription: xiv, 356 pages : illustrations ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9783319584867
Subject(s): DDC classification:
  • 006.3 ER.I 2017 23
LOC classification:
  • TL243 G85 2018
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.
Summary: "This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated second edition also includes new material on deep learning. Topics and features: Presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website; contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons;iIncludes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; reports on developments in deep learning, including applications of neural networks to generate creative content such as text, music and art (NEW); examines performance evaluation of clustering algorithms, and presents two practical examples explaining Bayestheorem and its relevance in everyday life (NEW); discusses search algorithms, analyzing the cycle check, explaining route planning for car navigation systems, and introducing Monte Carlo Tree Search (NEW); Includes a section in the introduction on AI and society, discussing the implications of AI on topics such as employment and transportation (NEW). Ideal for foundation courses or modules on AI, this easy-to-read textbook offers an excellent overview of the field for students of computer science and other technical disciplines, requiring no more than a high-school level of knowledge of mathematics to understand the material. Dr. Wolfgang Ertel is a professor at the Institute for Artificial Intelligence at the Ravensburg-Weingarten University of Applied Sciences, Germany."--Back cover.
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Item type Current library Collection Call number Status Date due Barcode
Books Books The Knowledge Hub Library Computing 006.3 ER.I 2017 (Browse shelf(Opens below)) Available 190347

Translated from the German "Grundkurs künstliche Intelligenz.

Includes bibliographical references (pages 339-349) and index.

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.

"This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated second edition also includes new material on deep learning. Topics and features: Presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website; contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons;iIncludes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; reports on developments in deep learning, including applications of neural networks to generate creative content such as text, music and art (NEW); examines performance evaluation of clustering algorithms, and presents two practical examples explaining Bayestheorem and its relevance in everyday life (NEW); discusses search algorithms, analyzing the cycle check, explaining route planning for car navigation systems, and introducing Monte Carlo Tree Search (NEW); Includes a section in the introduction on AI and society, discussing the implications of AI on topics such as employment and transportation (NEW). Ideal for foundation courses or modules on AI, this easy-to-read textbook offers an excellent overview of the field for students of computer science and other technical disciplines, requiring no more than a high-school level of knowledge of mathematics to understand the material. Dr. Wolfgang Ertel is a professor at the Institute for Artificial Intelligence at the Ravensburg-Weingarten University of Applied Sciences, Germany."--Back cover.

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