Artificial Intelligence Books

This book contains a selected papers published in NLP. Papers describe current research in Thesaurus, IR, Multilingual IR and Corpus annotation.

This is a avaliable book for people interested in NLP research.

The authors explain how artificial intelligence involves seeing
something familiar in a new light. The challenge is to emulate
scripts built up over time and experience. There are significant
problems with programs which do not change as the result of
new knowledge. In addition, there are problems in computer
learning from failure. In practice, it is impossible to
articulate every possible error condition. Even if the knowledge
engineer could articulate every possible error, the next problem
is programming the computer system to do a multiplicity of
validations. Too many validations built into a system, can cause
the throughput to degrade substantially . When throughput
suffers, the overall efficiency of the system collapses.
This work is an important advance in artificial intelligence and
expert systems.

It is a great pleasure and honor to write the review for the book by Fette. I am a communication engineer who practiced and taught communication systems for the last 34 years. It is heartening to see the progress in radio communication as this has changed the life style of people at large. From analog to digital to programmable to software defined and now to intelligent (cognitive) radio design we are feeling the future changes as to how people might use the radio technologies in the next 25 years. By studing this book from Fette one can easily guess where radio technologies will be heading. This book, and "Cognitive Radio Architecture" by J. Mitola, have come almost at the same time. While this book provides a general and more technological overview of various aspects of Cognitive radio, the book by J. Mitola gives specific architectural overview of the future radio. I feel both the books are must for those interested in studying and researching in the field of Radio Design both for commercial and military applications. My conclusion is that for Fifth Generation Cellular Radio these are the books to start with. Complimented by the research Articles (e.g. IEEE papaers) one can correctly find the way to radio development. I first congratulate Joseph Mitola for providing the lead in Software Defined/Cognitive radio concepts, and then appreciate the writer Fette for providing an excellent description of Cognitive radio with provision of connection to Software Defoined radio.
I am prticularly interested in Learning Strategies which modify the knowledgebase for making good decision to provide desired QoS in mobile communication systems (environment).
My congratualtions to both J. Mitola and Fette as they have given us the timely information on the subject.
Thank you.

This is a very interesting book allowing one to look at the future (from the 1940s) from Alan Turing's frame of mind.

There is a lot of unintended humor here. Computers are people who do calculations. Computer programs are "instruction tables". The imminent demise of the mathematicians who write the instruction tables (because the machine can eventually write its own) leads to the creation of gibberish (computerese).

If Turing could only imagine his brainchild would end up as an internet appliance... or a game platform. I think he would be amazed and pleased.

This book contains interesting LISP source code. The title say about Neural Networks and chaos, but the Chaos chapter is very small. However, this book contains a game!!. The Chess program (not use neural networks) is written totally in LISP. And play good. You can study the search techniques. I recommend this book for LISP lovers.

As claimed by the author of Computational Intelligence for Decision Support, the objective of this book was to provide an integrated approach for decision making. This is not an easy task, and the author did a commendable job. With less than 400 pages, the book contains rich contents, ranging from data management to knowledge management, all presented in a concise manner. More importantly, the author has put emphasis on the thinking process in problem solving. Numerous small examples can be found throughout the book. The book not only presents "mainstream" AI, but "sidetrack" AI as well. Many interesting topics, including discussion related to computational support for creativity, cannot be found in any existing AI books with the similar scope. By integrating problem solving paradigms dealing with data as well as knowledge, readers are given a unique opportunity to explore both disciplines in a single volume. In addition, this book also serves as a useful reference book for recent development several related areas, such as data warehousing and data mining, as well as information retrieval on semi-structured data (as is found in today's Internet).

Some arguments in the book are from the author's personal perspective, and may or may not be acceptable to everybody. Nevertheless, after examination of this book, my recommendation to everybody is: if you are interested in a holistic exposure of problem solving using information technology, waste no time to get a copy of this book and read it!

Excellent book. I highly recommend it. Although Computational Intelligence could include almost any subject, this book is a comprehensive review of the most agreed-upon paradigms in CI. Haven't checked out the CD that comes with the book, so I cannot comment about it.

Chapter 4 of this book is the pot of gold: A concrete, detailed description of how the cerebral cortex works. Thinking relies upon an operation which could be called confabulation (in the chapter it is called concensus building). THIS IS NOT REASONING (at least in any classical sense). Yet, because the simple kind of knowledge used (antecedent support probabilities) is exhaustive, concensus building yields excellent conclusions. This cortical theory also shows why AI has failed: reasoning is too difficult and requires too much knowledge of an expensive type. Cortex gets by with a much simpler type of knowledge (which only concerns pairs of object and action attributes, not n-tuples) which, while it is needed in huge quantities, is easy to obtain. An implication of this corticl theory is that we can now proceed to develop successful AI by adopting this cortical design. The theory is illustrated by means of computer thinking experiments that yield compelling results (and which readers can replicate).

If, as I believe, persons enjoy what they do well, then Dr. Paul Thagard must enjoy computational philosophy of science very much. Computational philosophy of science is the new frontier in philosophy of science today, and it portends to become essential to and definitive of twenty-first century philosophy of science.

Thagard is one of the few academic philosophers of science who has demonstrated the requisite technical skills in computer systems analysis to make contributions to this new area. I believe that all of his works are worth reading, and this Introduction should be requisite reading for the graduate student in philosophy of science preparing for the twenty-first century. Five stars are not enough!

Readers interested in my commentary on Thagard are to view my online book titled History of Twentieth-Century Philosophy of Science at my com web site philsci with free downloads.

Thomas J. Hickey

The book is well-written, easy-to-read, clear. What's that worth for a technical subject? Just about everything. First, it means you can read it like a novel, effortlessly (nearly). Second, you get a clear picture of what he is saying. So the value is there.