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Introduction to Artificial Intelligence: 2017
£39.99

INTRODUCTION TO ARTIFICIAL INTELLIGENCE: 2017

PAPERBACK BY ERTEL, WOLFGANG; BLACK, NATHANAEL T.

£39.99

ISBN
9783319584867
IMPRINT
SPRINGER INTERNATIONAL PUBLISHING AG
 
 
EDITION
2ND REVISED EDITION
PUBLISHER
SPRINGER INTERNATIONAL PUBLISHING AG
STOCK FOR DELIVERY
LOW STOCK
FORMAT
PAPERBACK
PAGES
311 pages
PUBLICATION DATE
17 AUG 2017

DESCRIPTION

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; includes 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 Bayes' theorem 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.

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