Modeling Bounded Rationality (Zeuthen Lecture Book Series) Review

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(More customer reviews)Very well written in terms of technical coverage and originality of modelling bounded rationality and its application to game theory. However, the author develops most of his theories from either assumption and speculation or no justification at all in terms of formally depicting human rationality. It would have been a much more powerful book if there was a greater coverage of empirical evidence and bridging between psychology, artificial intelligence and economics. This lop-sided approach of modelling using solely game theoretic terminology and concepts ambiguous in their relevancy to simulating human thought and behaviour. However, there are some chapters, such as the one on knowledge representation and the other on limited memory that are the exception to this. Overall though, the book is still quite innovative and worth a read.

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The notion of bounded rationality was initiated in the 1950's by Herbert Simon. In this book the author defines models of bounded rationality as those in which elements of the process of choice are explicitly embedded. The book focuses on the challenges of modelling bounded rationality, rather than on substantial economic implications. In the first part of the book the author considers the modelling of choice. After discussing some psychological findings, he proceeds to the modelling of procedural rationality, knowledge, memory, the choice of what to know and group decisions. In the second part, he discusses the fundamental difficulties of modelling bounded rationality in games. He begins with the modelling of a game with procedural rational players and then surveys repeated games with complexity considerations. He ends with a discussion of computability constraints in games. The final chapter includes a critique by Herbert Simon of the author's methodology and the author's response.

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Artificial Intelligence and Soft Computing: Behavioral and Cognitive Modeling of the Human Brain Review

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(More customer reviews)The book by Amit Konar is a new addition to the disciplines of Artificial Intelligence and Soft Computing. I am greatly charmed with the presentation style of the author. The chapters onImprecision and Uncertainty Management (ch.9), Fuzzy Petrinet (ch.10), Spatial and temporal Reasoning (ch.11), neural nets. (ch.14) and genetic algorithm (ch.15) impressed me much both for their simplicity and research-orientation. The book started with a humble beginning on psychological model of perception in chapter 2, and introduced many new concepts to formalize the theory of perception. The last two chapters in the book deal with applications of cognitive science in a criminology application and navigational planning of mobile robots respectively. The CD included with the book contains the programs used to demonstrate the concepts of the last two chapters. The programs can easily be run even by a novice user with the guidelines presented in Appendix-A.I wish you will enjoy reading this valuable book, the price paid for which is justified enough.

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With all the material available in the field of artificial intelligence (AI) and soft computing-texts, monographs, and journal articles-there remains a serious gap in the literature. Until now, there has been no comprehensive resource accessible to a broad audience yet containing a depth and breadth of information that enables the reader to fully understand and readily apply AI and soft computing concepts.Artificial Intelligence and Soft Computing fills this gap. It presents both the traditional and the modern aspects of AI and soft computing in a clear, insightful, and highly comprehensive style. It provides an in-depth analysis of mathematical models and algorithms and demonstrates their applications in real world problems. Beginning with the behavioral perspective of "human cognition," the text covers the tools and techniques required for its intelligent realization on machines. The author addresses the classical aspects-search, symbolic logic, planning, and machine learning-in detail and includes the latest research in these areas. He introduces the modern aspects of soft computing from first principles and discusses them in a manner that enables a beginner to grasp the subject. He also covers a number of other leading aspects of AI research, including nonmonotonic and spatio-temporal reasoning, knowledge acquisition, and much more. Artificial Intelligence and Soft Computing: Behavioral and Cognitive Modeling of the Human Brain is unique for its diverse content, clear presentation, and overall completeness. It provides a practical, detailed introduction that will prove valuable to computer science practitioners and students as well as to researchers migrating to the subject from other disciplines.

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AI for Computer Games and Animation: A Cognitive Modeling Approach Review

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(More customer reviews)When I bought this book I wasn't quite sure what to expect since the title, "AI for Games and Animation: ..." is so broad sounding. What I did expect was that it would be written in an easy to read form and hopefully provide enough in-depth coverage of the topics so that a reasonable game programmer could implement them based on the information provided, without further research. This criteria seems to be adhered to in the technical articles in a publication such as Game Developer.
Apparently, no-one bothered to tell Mr. Funge about this. Although the book does provide some case studies (examples) the actual details of their implementations are often glossed over or shrouded in unnecessary mathematical formalism that is out of place in a game programmer's book. To give an example, complex topics such as inverse kinematics and coupled spring systems are given several short paragraphs. In describing coupled spring systems for deforming a mesh, Funge uses "x dot" notation that most game programmers probably are not familiar with.
The only saving grace is the reference section which can point the reader to more specific literature that may actually be helpful in constructing implementations of some of the techniques described in the book. This increases the rating from the worst (1 star) to 2 stars since it is actually pretty comphrensive.

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John Funge introduces a new approach to creating autonomous characters. Cognitive modeling provides computer-animated characters with logic, reasoning, and planning skills. Individual chapters in the book provide concrete examples of advanced character animation, automated cinematography, and a real-time computer game. Source code, animations, images, and other resources are available at the book's website, listed below.

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