- Hardcover: 236 pages
- Publisher: iUniverse.com (1 Nov 2002)
- Language English
- ISBN-10: 0595654371
- ISBN-13: 978-0595654376
- Product Dimensions: 23.6 x 16.4 x 2.1 cm
- Amazon Bestsellers Rank: 3,773,380 in Books (See Top 100 in Books)
- See Complete Table of Contents
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More About the Author
Product Description
Product Description
"AI4U: Mind-1.1 Programer's Manual" has the following positive and negative points. + It describes the rapidly evolving AI Minds on the Web. - It quickly becomes obsolete as the AI hyper-evolves. + On-demand publishing (ODP) makes for quick updates. - The Mentifex project is considered oddball on the 'Net. + You've got the first book about the first real AI Mind. - There are other, better, more authoritative AI textbooks. + AI4U makes a good supplement for actually coding AI. - Artificial intelligence is too hard to understand. + AI4U describes the AI while it is still easy to learn. - "I would rather build robots than study AI programming." + If you want to build a smart robot, then AI4U is for you. - "I'm only a high school student/teacher; what's the use?" + This book will challenge even the most gifted student. - "I am not a programmer and so I can't code AI." + AI4U teaches you how to operate an AI, not just code it. - "I just want to do Web design, not artificial intelligence." + AI4U provides an AI that you may install on your website. - "I am more interested in neuroscience and/or psychology." + AI4U teaches a theory of how the brain works psychologically.
From the Author
AI4U: Mind-1.1 Programmer's Manual is a supplemental or stand-alone AI textbook with 34 chapters -- one for each of the 34 mind-modules of the tutorial artificial Mind-1.1 release. Each chapter starts with a brain-mind theory diagram to illustrate the mental process taking place in the implemented mind-module, and ends with AI laboratory/homework exercises ranging from the immediately practical to the most ambitious dreams of your AI imagination. The book as a whole introduces a
linguistic theory of mind (TOM) for AI. An epilogue on consciousness features a system diagram of the entire artificial mind. Although the complete JavaScript source code of the Mind-1.1 release is listed in the AI4U textbook so that computer science students may study the algorithm of any mind-module, there is no need to scan or key in the
code, because it is freely available on the Web as public-domain AI software that runs in the MSIE (Microsoft Internet Explorer) browser. The purchase of the First Edition AI4U book eliminates the need for Mind-1.1 users to pay a shareware fee for the free AI source code available by searching for "Mentifex" on the World Wide Web or by visiting the open-source "Mind" project at SourceForge. --This text refers to the Paperback edition.
linguistic theory of mind (TOM) for AI. An epilogue on consciousness features a system diagram of the entire artificial mind. Although the complete JavaScript source code of the Mind-1.1 release is listed in the AI4U textbook so that computer science students may study the algorithm of any mind-module, there is no need to scan or key in the
code, because it is freely available on the Web as public-domain AI software that runs in the MSIE (Microsoft Internet Explorer) browser. The purchase of the First Edition AI4U book eliminates the need for Mind-1.1 users to pay a shareware fee for the free AI source code available by searching for "Mentifex" on the World Wide Web or by visiting the open-source "Mind" project at SourceForge. --This text refers to the Paperback edition.
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Amazon.com:
3 reviews
31 of 36 people found the following review helpful
The rantings of a crackpot.
13 April 2005
Format:Hardcover
There is no polite way to say this. The author is a crackpot. Reading the materials he provides on his website, an astute reader will notice several things. Firstly, this person doesn't know how to design software at all. He also presumes that his reader knows even less than he does. The "AI" he proposes is nothing more than a basic for(;;) loop. (One of the primitive constructs provided by C, C++, Java and their dirivitives...). He is aware of some of the limititations of his design but is unaware of their obvious (to any intermediate-level programmer) work-arounds. Secondly, while he is happy to put lavish names, such as "Sensorium", on empty or nearly empty functions, he seems to be completely oblivious to the real issues a succesful AI mind must address.
He throws about refferances to concepts in the AI and futurist community such as the technological singularity but fails to demonstrate any understanding of what they mean. He claims that his design solves the AI problem when, infact, it hardly does anything at all.
He claims that his system is suitable for use in robotics, yet he has done no orrigional experamentation.
He continues to troll the usenet (sending between 5-7 messages to every AI and transhumanism related newsgroup per month) pushing his book and his lame ideas.. (If his ideas had even a tenth the merit he claims he would be world-famous...)
I am an AI enthuseast myself and hope to, oneday, publish my own work on the subject. (you can find some of my writings on my website). I do not have the audacity to claim that my work is yet worth anything because I have not yet made much progress. In general, you should stay away from all books on AI unless they are based on actual work that has been done in the field. Work, in this case, being either hard research on biological systems or software development efforts that have shown some type of results.
He throws about refferances to concepts in the AI and futurist community such as the technological singularity but fails to demonstrate any understanding of what they mean. He claims that his design solves the AI problem when, infact, it hardly does anything at all.
He claims that his system is suitable for use in robotics, yet he has done no orrigional experamentation.
He continues to troll the usenet (sending between 5-7 messages to every AI and transhumanism related newsgroup per month) pushing his book and his lame ideas.. (If his ideas had even a tenth the merit he claims he would be world-famous...)
I am an AI enthuseast myself and hope to, oneday, publish my own work on the subject. (you can find some of my writings on my website). I do not have the audacity to claim that my work is yet worth anything because I have not yet made much progress. In general, you should stay away from all books on AI unless they are based on actual work that has been done in the field. Work, in this case, being either hard research on biological systems or software development efforts that have shown some type of results.
19 of 22 people found the following review helpful
A charlatan's bible
14 July 2005
Format:Hardcover
From any decent developer, you would expect something, which would at least compare to Winograd's SHRDLU. For some reason, the book however is failing to show any results of the "software-architecture" being explained in length!
A scientist's moral dictates, that you withdraw your theories, if you have been proven wrong. Arthur T. Murray however doesn't show any inclination to do so. Instead he is still continuously advertising his long ago falsified book in forums and he's claiming to have developed a powerful approach to AI.
I think, I can safely say, that the author is a phoney and he's only trying to sell his book. So take my advice and don't by it (as I did)!
A scientist's moral dictates, that you withdraw your theories, if you have been proven wrong. Arthur T. Murray however doesn't show any inclination to do so. Instead he is still continuously advertising his long ago falsified book in forums and he's claiming to have developed a powerful approach to AI.
I think, I can safely say, that the author is a phoney and he's only trying to sell his book. So take my advice and don't by it (as I did)!
8 of 9 people found the following review helpful
A Review of AI4U
30 Nov 2006
Format:Paperback|Amazon Verified Purchase
Murray believes that with the spread of activation
through a network of the correct configuration and
sufficient size you have intelligence and thought.
Not everyone would start from that premise but
probably most connectionist do. While AI4U is
sometimes advertised as a "textbook" it is not
that. An AI textbook should discuss at least the
core AI topics:
search
pattern recognition
knowledge representation
learning
logic
rule-based systems
neural networks
etc.
While AI4U touches on some of these topics it
is not an adequate textbook. Rather it is a
defence of one man's approach to building an
artificial intelligence.
The chapters in this book are too brief and
the discussions too superficial. There also need
to be algorithms provided for each routine in the
code of Appendix A. These could be presented in
pseudocode or as flowcharts for instance.
The biggest problem is the lack of references.
It is just possible that one could write a short
note without finding it necessary to reference the
work of others but it is impossible to write a book
length scholarly work without citing other work in
the field. This is a fatal flaw. Murray should
begin by referencing:
The Structure of Long-term Memory, W. Klimesh,
Lawrence Erlbaum, 1994
Netl, S. E. Fahlman, MIT Press, 1979
Adaptive Information Retrieval, R. K. Belew, U. of
Michigan, PhD thesis, 1986
The authors of these works have accomplished some
of the things Murray is trying to do with Mentifex.
A positive side to Murray's work is that he does
provide downloadable code. When you run this code you
find that Mentifex is very slow even with a very small
semantic network. If one were to build up the millions
of nodes needed to approach human level intelligence
the code would grind to a halt. Murray seems to think
running Mentifex on parallel processors will solve
this problem. I calculate that it will not. I
believe human level preformance requires that one
apply multiple approaches to controling complexity:
category formation by clustering/vector quantization
hierarchical knowledge organization/processing
parallel processing
avoiding search whenever possible
simultaneous use of multiple specialized agents
sequential running of multiple generations of agents
plus any other means you can bring to bear.
(see Asa H, R. Jones, Transactions of the Kansas
Academy of Science, vol 109, No. 3/4, pg 159, 2006)
through a network of the correct configuration and
sufficient size you have intelligence and thought.
Not everyone would start from that premise but
probably most connectionist do. While AI4U is
sometimes advertised as a "textbook" it is not
that. An AI textbook should discuss at least the
core AI topics:
search
pattern recognition
knowledge representation
learning
logic
rule-based systems
neural networks
etc.
While AI4U touches on some of these topics it
is not an adequate textbook. Rather it is a
defence of one man's approach to building an
artificial intelligence.
The chapters in this book are too brief and
the discussions too superficial. There also need
to be algorithms provided for each routine in the
code of Appendix A. These could be presented in
pseudocode or as flowcharts for instance.
The biggest problem is the lack of references.
It is just possible that one could write a short
note without finding it necessary to reference the
work of others but it is impossible to write a book
length scholarly work without citing other work in
the field. This is a fatal flaw. Murray should
begin by referencing:
The Structure of Long-term Memory, W. Klimesh,
Lawrence Erlbaum, 1994
Netl, S. E. Fahlman, MIT Press, 1979
Adaptive Information Retrieval, R. K. Belew, U. of
Michigan, PhD thesis, 1986
The authors of these works have accomplished some
of the things Murray is trying to do with Mentifex.
A positive side to Murray's work is that he does
provide downloadable code. When you run this code you
find that Mentifex is very slow even with a very small
semantic network. If one were to build up the millions
of nodes needed to approach human level intelligence
the code would grind to a halt. Murray seems to think
running Mentifex on parallel processors will solve
this problem. I calculate that it will not. I
believe human level preformance requires that one
apply multiple approaches to controling complexity:
category formation by clustering/vector quantization
hierarchical knowledge organization/processing
parallel processing
avoiding search whenever possible
simultaneous use of multiple specialized agents
sequential running of multiple generations of agents
plus any other means you can bring to bear.
(see Asa H, R. Jones, Transactions of the Kansas
Academy of Science, vol 109, No. 3/4, pg 159, 2006)
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