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Introduction to artificial intelligence

Author: Wolfgang Ertel; Nathanael Black; Florian Mast
Publisher: Cham, Switzerland : Springer, [2017] ©2017
Series: Undergraduate topics in computer science.
Edition/Format:   Print book : English : Second editionView all editions and formats
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,  Read more...
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Document Type: Book
All Authors / Contributors: Wolfgang Ertel; Nathanael Black; Florian Mast
ISBN: 9783319584867 3319584863
OCLC Number: 1022949011
Language Note: Translated from the German.
Description: xiv, 356 pages : illustrations (some color) ; 24 cm.
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.
Series Title: Undergraduate topics in computer science.
Other Titles: Grundkurs künstliche Intelligenz.
Responsibility: Wolfgang Ertel ; translated by Nathanael Black ; with illustrations by Florian Mast.

Abstract:

"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."--Back cover.

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