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Introduction to Artificial Intelligence: Undergraduate Topics in Computer Science

Autor Wolfgang Ertel Traducere de Nathanael T. Black
en Limba Engleză Paperback – 27 aug 2024
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 third 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 
·        Introduces convolutional neural networks as the currently most important type of deep learning networks with applications to image classification (NEW) 
·        Contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons 
·        Reports on developments in deep learning, including applications of neural networks to large language models as used in state-of-the-art chatbots as well as to the generation of music and art (NEW) 
·        Includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks, and reinforcement learning
 ·        Covers various classical machine learning algorithms and introduces important general concepts such as cross validation, data normalization, performance metrics and data augmentation (NEW)
·       Includes a section on AI and society, discussing the implications of AI on topics such as employment and transportation  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.
 

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Specificații

ISBN-13: 9783658431013
ISBN-10: 3658431016
Pagini: 425
Ilustrații: Approx. 425 p.
Dimensiuni: 155 x 235 mm
Greutate: 0.68 kg
Ediția:3rd ed. 2024
Editura: Springer Fachmedien Wiesbaden
Colecția Springer
Seria Undergraduate Topics in Computer Science

Locul publicării:Wiesbaden, Germany

Cuprins

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.

Notă biografică

Dr. Wolfgang Ertel is a professor at the Institute for Artificial Intelligence at the Ravensburg-Weingarten University of Applied Sciences, Germany.

Textul de pe ultima copertă

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 third 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 
·        Introduces convolutional neural networks as the currently most important type of deep learning networks with applications to image classification (NEW) 
·        Contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons 
·        Reports on developments in deep learning, including applications of neural networks to large language models as used in state-of-the-art chatbots as well as to the generation of music and art (NEW) 
·        Includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks, and reinforcement learning
 ·        Covers various classical machine learning algorithms and introduces important general concepts such as cross validation, data normalization, performance metrics and data augmentation (NEW)
·       Includes a section on AI and society, discussing the implications of AI on topics such as employment and transportation 
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.
 


Caracteristici

A concise, quick resource on A.I., excellent for courses and professional self-study Presents an application-focused and hands-on approach to learning the subject Provides study exercises, highlighted examples, definitions, theorems, and illustrative cartoons