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New Applications of Artificial Intelligence (Pedro Ponce, et al)
This book shows the newest applications reached according with the technological changes that are presented nowadays. Those changes drastically appear in digital systems or other parallel areas that allow to improve the performance of AI algorithms.

Artificial Intelligence: Foundations of Computational Agents
This is a a textbook aimed at junior to senior undergraduate students and firstyear graduate students. It presents artificial intelligence (AI) using a coherent framework to study the design of intelligent computational agents.

AI Algorithms, Data Structures, and Idioms in Prolog, Lisp, and Java
Illustrateing how to program AI algorithms in Lisp, Prolog, and Java. Topics include: simple productionlike system based on logic, logicbased learning, and natural language parsing.

Practical Artificial Intelligence Programming in Java (Mark Watson)
This book uses both best of breed open source software and the author's own libraries to introduce the reader to Artificial Intelligence (AI) technologies like genetic algorithms, neural networks, expert systems, machine learning, etc.

Computers and Thought: An Introduction to Artificial Intelligence
This book provides a unified, selfcontained introduction to artificial intelligence for readers with little or no computing background.

Building the Second Mind: The Origins of Artificial Intelligence
This book tells the history of the origins of Artificial Intelligence (AI). As the field that seeks to do things that would be considered intelligent if a human being did them, AI is a constant of human thought.

Clever Algorithms: NatureInspired Programming Recipes
The book describes 45 algorithms from the field of Artificial Intelligence. All algorithm descriptions are complete and consistent to ensure that they are accessible, usable and understandable by a wide audience.

Artificial Intelligence: Structures and Strategies (George F. Luger)
This book captures the essence of artificial intelligence  solving the complex problems that arise wherever computer technology is applied. Readers learn how to use a number of different software tools and techniques to address many challenges.

The Future of Machine Intelligence (David Beyer)
This exclusive report unpacks concepts and innovations that represent the frontiers of eversmarter machines. You’ll get a rare glimpse into this exciting field through the eyes of some of its leading minds.

The LION Way: Machine Learning Plus Intelligent Optimization
This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to people in both fields. Optimization approaches have enjoyed prominence in machine learning.

Modeling Creativity  Case Studies in Python (Tom De Smedt)
This book is to model creativity using computational approaches in Python. The aim is to construct computer models that exhibit creativity in an artistic context, that is, that are capable of generating or evaluating an artwork (visual or linguistic), etc.

Simply Logical: Intelligent Reasoning by Example (Peter Flach)
This book is an introduction to Prolog programming for artificial intelligence covering both basic and advanced AI material.

Inductive Logic Programming: Techniques and Applications
This book is an introduction to inductive logic programming (ILP), which aims at a formal framework as well as practical algorithms for inductively learning relational descriptions in the form of logic programs.

Introduction to Soft Computing (Eva Volna)
This book gives an introduction to Soft Computing, which aims to exploit tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve close resemblance with human like decision making.

Learning Deep Architectures for AI (Yoshua Bengio)
This book discusses the motivations for and principles of learning algorithms for deep architectures. By analyzing and comparing recent results with different learning algorithms for deep architectures, explanations for their success are proposed.

Reinforcement Learning: An Introduction, Second Edition
This textbook provides a clear and simple account of the key ideas and algorithms of reinforcement learning that is accessible to readers in all the related disciplines. Familiarity with elementary concepts of probability is required.

Logic Programming in Scheme (Nils M. Holm)
Questions answered in this little book: What is logic programming? Why is negation hard in logic programming? What is cutting? How do I solve logic puzzles? How is logic programming implemented?

Expert Systems in Prolog (Dennis Merritt)
For Prolog programmer interested in either building expert systems or experimenting with various expert system techniques. using a stepbystep approach to building systems, explaining the concepts and showing the Prolog code at each stage.

From Bricks to Brains: Embodied Cognitive Science of LEGO Robots
This book introduces embodied cognitive science and illustrates its foundational ideas through the construction and observation of LEGO Mindstorms robots.

Mind, Body, World: Foundations of Cognitive Science (M. Dawson)
Intended to introduce both graduate and senior undergraduate students to the foundations of cognitive science, Mind, Body, World addresses a number of questions currently being asked by those practicing in the field.

Planning Algorithms (Steven M. LaValle)
This is the only book for teaching and referencing of Planning Algorithms in applications including robotics, computational biology, computer graphics, manufacturing, aerospace applications and medicine, etc.

The Quest for Artificial Intelligence: Ideas and Achievements
This book traces the history of the subject, from the early dreams of eighteenthcentury (and earlier) pioneers to the more successful work of today's AI engineers.

Artificial Intelligence and Molecular Biology (Lawrence Hunter)
A brief introductory primer on molecular biology and Al gives computer scientists sufficient background to understand much of the biology discussed in the book.

A Field Guide to Genetic Programming (Riccardo Poli, et al)
This book to provides a complete and coherent review of the theory of genetic programming (GP). It is written by three of the most active scientists in GP.

Genetic Programming  New Approaches and Successful Applications
The purpose of this book is to show recent advances in the field of GP, both the development of new theoretical approaches and the emergence of applications that have successfully solved different real world problems.

Fuzzy Logic  Emerging Technologies and Applications (E. P. Dadios)
This book shows various applications of Fuzzy Logic in the field of Bioinformatics, Health, Security, Communications, Transportations, Financial Management, Energy and Environment Systems.

Genetic Algorithms in Applications (Rustem Popa)
This wellorganized book takes the reader through the new and rapidly expanding field of genetic algorithms step by step, from a discussion of numerical optimization, to a survey of current extensions to genetic algorithms and applications.

BioInspired Computational Algorithms and Their Applications
Integrates contrasting techniques of genetic algorithms, artificial immune systems, particle swarm optimization, and hybrid models to solve many realworld problems.

An Introduction to Logic Programming Through Prolog (J. M. Spivey)
This is one of the few texts that combines three essential theses in the study of logic programming: logic, programming, and implementation.

Common LISP: A Gentle Introduction to Symbolic Computation
This highly accessible introduction to Lisp is suitable both for novices approaching their first programming language and experienced programmers interested in exploring a key tool for artificial intelligence research.

A Quick and Gentle Guide to Constraint Logic Programming
This is an introductory and downtoearth presentation of Constraint Logic Programming (CLP), for solving combinatorial as well as continuous constraint satisfaction problems and constraint optimization problems.

Conceptive C (Harry McGeough)
Conceptive C is an AI programming Language based on ObjectiveC and C Language. It is a superset of both languages and is designed to work with Apple Mac OS X and iOS.

Essentials of Metaheuristics (Sean Luke)
This book is an open set of lecture notes on metaheuristics algorithms, intended for undergraduate students, practitioners, programmers, and other nonexperts.

Shape Interrogation for Computer Aided Design and Manufacturing
This book provides the mathematical fundamentals as well as algorithms for various shape interrogation methods including nonlinear polynomial solvers, intersection problems, differential geometry of intersection curves, distance functions, etc.

Machine Learning, Neural and Statistical Classification (D. Michie)
Statistical, machine learning and neural network approaches to classification are all covered in this volume.

Machine Learning Using C# Succinctly (James McCaffrey)
This book shows several different approaches to applying machine learning to data analysis and prediction problems. It also demonstrates different clustering and classification techniques, and explains how effective these techniques can be.

A Course in Machine Learning (Hal Daum� III)
This is a set of introductory materials that covers most major aspects of modern machine learning (supervised learning, unsupervised learning, large margin methods, probabilistic modeling, learning theory, etc.).

Global Optimization Algorithms  Theory and Application. 2nd Edition
This book is devoted to global optimization algorithms, which are methods to find optimal solutions for given problems.

Recent Advances in Face Recognition (Kresimir Delac, et al)
This book provides a broad overview on face recognition and identified trends for future developments and the means for implementing robust systems..

Logic, Programming and Prolog, 2nd Edition (Ulf Nilsson, et al)
This book introduces major new developments in a continually evolving field and includes such topics as concurrency and equational and constraint logic programming.

Logic for Computer Science: Automatic Theorem Proving (J. Gallier)
This book covers the mathematical logic necessary to computer science, emphasizing algorithmic methods for solving proofs.

Artificial Intelligence and Logic Programming
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