Introduction to artificial intelligence (Undergraduate topics in computer science)

This concise and accessible textbook supports a foundation or module course on A.I., covering a broad selection of the subdisciplines within this field. The book presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning.
Topics and features: presents an application-focused and hands-on approach to learning the subject, provides study exercises of varying degrees of difficulty at the end of each chapter, with solutions given at the end of the book, supports the text with highlighted examples, definitions, and theorems, includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning, contains an extensive bibliography for deeper reading on further topics, supplies additional teaching resources, including lecture slides and training data for learning algorithms, at an associated website.

Introduction

From the reviews:'The book is aimed primarily at undergraduates who have not yet taken linear algebra or multidimensional calculus. ... it contains many exercises with solutions at the back, thus, it supports self-learning. ... The many excellent figures, some in color, help make the material easily understandable. A companion Web site contains supplementary materials, such as program code for the book, most of which is in or commented on in German. Summing Up: Recommended. Upper-division undergraduates and above.' (S. L. Tanimoto, Choice, Vol. 49 (2), October, 2011)