Artificial Intelligence is the study of how to build or program computers to enable them to do what minds can do. This volume discusses the ways in which computational ideas and computer modeling can aid our understanding of human and animal minds. Major theoretical approaches are outlined, as well as some promising recent developments. Fundamental philosophical questions are discussed along with topics such as: the differences between symbolic and connectionist AI, planning and problem solving, knowledge representation, learning, expert systems, vision, natural language, creativity, and human-computer interaction. This volume is suitable for any psychologist, philosopher, or computer scientist wanting to know the current state of the art in this area of cognitive science.

Key Features
* Up-to-date account of how computational ideas and techniques are relevant to psychology
* Includes discussions of "classical" (symbolic) AI, of connectionism (neural nets), of evolutionary programming, and of A-Life
* Discusses a wide range of psychology from low-level vision to creativity

The information deluge currently assaulting us in the 21st century is having a profound impact on our lifestyles and how we work. We must constantly separate trustworthy and required information from the massive amount of data we encounter each day. Through mathematical theories, models, and experimental computations, Artificial Intelligence with Uncertainty explores the uncertainties of knowledge and intelligence that occur during the cognitive processes of human beings. The authors focus on the importance of natural language-the carrier of knowledge and intelligence-for artificial intelligence (AI) study. This book develops a framework that shows how uncertainty in AI expands and generalizes traditional AI. It describes the cloud model, its uncertainties of randomness and fuzziness, and the correlation between them. The book also centers on other physical methods for data mining, such as the data field and knowledge discovery state space. In addition, it presents an inverted pendulum example to discuss reasoning and control with uncertain knowledge as well as provides a cognitive physics model to visualize human thinking with hierarchy. With in-depth discussions on the fundamentals, methodologies, and uncertainties in AI, this book explains and simulates human thinking, leading to a better understanding of cognitive processes

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Book Description
Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments. The main focus of this **** is centred on the computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation.

Engelbrecht provides readers with a wide knowledge of Computational Intelligence (CI) paradigms and algorithms; inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without any difficulty through a single Java class as part of the CI library.

Key features of this second edition include:

* A tutorial, hands-on based presentation of the material.
* State-of-the-art coverage of the most recent developments in computational intelligence with more elaborate discussions on intelligence and artificial intelligence (AI).
* New discussion of Darwinian evolution versus Lamarckian evolution, also including swarm robotics, hybrid systems and artificial immune systems.
* A section on how to perform empirical studies; topics including statistical analysis of stochastic algorithms, and an open source library of CI algorithms.
* Tables, illustrations, graphs, examples, assignments, Java code implementing the algorithms, and a complete CI implementation and experimental framework.

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Artificial Intelligence: A Systems Approach (w/CDROM)(Computer Science) (Engineering)(AI) (Engineering)
By Jones
* Publisher: Infinity Science Press
* Number Of Pages: 498
* Publication Date: 2007-12-21
* ISBN-10 / ASIN: 0977858235
* ISBN-13 / EAN: 9780977858231
Product Description:
This book offers students and AI programmers a new perspective on the study of artificial intelligence concepts. The essential topics and theory of AI are presented, but it also includes practical information on data input & reduction as well as data output (i.e., algorithm usage). Because traditional AI concepts such as pattern recognition, numerical optimization and data mining are now simply types of algorithms, a different approach is needed. This sensor / algorithm / effecter approach grounds the algorithms with an environment, helps students and AI practitioners to better understand them, and subsequently, how to apply them. The book has numerous up to date applications in game programming, intelligent agents, neural networks, artificial immune systems, and more. A CD-ROM with simulations, code, and figures accompanies the book. *Features *Covers not only AI theory, but modern applications e.g., game programming, machine learning, swarming, artificial immune systems, genetic algorithms, pattern recognition, numerical optimization, data mining, and more *Discusses the various computer languages of AI from LISP to JAVA and Python *Includes a CD-ROM with 100MB ofsimulations, code, and fi gures *Table of Contents 1. Introduction. 2. Search. 3. Games. 4. Logic. 5. Planning. 6. Knowledge Representation. 7. Machine Learning. 8. Probabilistic Reasoning. 9. Stochastic Search. 10. Neural Networks. 11.
Intelligent Agents. 12. Hybrid Models. 13. Languages of AI.

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