- Taschenbuch: 532 Seiten
- Verlag: Basic Books (22. März 1996)
- Sprache: Englisch
- ISBN-10: 0465024750
- ISBN-13: 978-0465024759
- Größe und/oder Gewicht: 19 x 3 x 24,8 cm
- Durchschnittliche Kundenbewertung: 3 Kundenrezensionen
- Amazon Bestseller-Rang: Nr. 187.338 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)
- Komplettes Inhaltsverzeichnis ansehen
Fluid Concepts And Creative Analogies: Computer Models Of The Fundamental Mechanisms Of Thought (Englisch) Taschenbuch – 22. März 1996
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Douglas Hofstadter, best known for his masterpiece Godel, Escher, Bach: An Eternal Golden Braid, tackles the subject of artificial intelligence and machine learning in his thought-provoking work Fluid Concepts and Creative Analogies, written in conjunction with the Fluid Analogies Research Group at the University of Michigan. Driven to discover whether computers can be made to "think" like humans, Hofstadter and his colleagues created a variety of computer programs that extrapolate sequences, apply pattern-matching strategies, make analogies, and even act "creative." As always, Hofstadter's work requires devotion on the part of the reader, but rewards him with fascinating insights into the nature of both human and machine intelligence.
Readers of earlier works by Douglas Hofstadter will find this book a natural extension of his style and his ideas about creativity and analogy; in addition, psychologists, philosophers, and artificial-intelligence researchers will find in this elaborate web of ingenious ideas a deep and challenging new view of mind.Alle Produktbeschreibungen
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If you're up to reading research-type papers on some very interesting projects, this book is very worthwhile.
when I first read his column Metamagical Themas, which ran in Scientific American from 1981 through 1983.
In that column, he tackled all manner of thought provoking subjects. In the interveneing years, he
has released some pretty meme-rich tomes, none for the faint of heart. From the far-out thought
experiments of The Minds Eye to the Pulitzer Prize winning Godel, Escher, Bach: An Eternal Golden Braid,
to his latest (reviewed here), Mr. Hofstadter always keeps the reader on his or her mental toes.
Many researchers in the field of Artificial Intelligence take the approach of attempting to mimick the
behavior of people with computer programs. On the surface, this might seem a logical direction to take, and so
AI researchers have a tendency to go and dream up batteries of tests that aim to characterize some area
of human behavior, then the sum up all the results and come up with the range of responses that fits cozily
into their bell-shaped curves. Armed with what they've assured themselves is normal human response to
all their scenerios, the go off and attempt to write computer programs that react the same way as John or
Jane Doe did. Once they've gotten a program that generally responds like 'most of the human subjects' did,
they usually beef it up by programming in more and more details about the domain of the scenerio at hand.
A good example of this line of thought is
Deep Blue, IBM's massively parallel chess playing supercomputer.
What Douglas Hofstader's latest book points out is that this sort of thinking about artificial intelligence is
the brute force approach. What you end up with is a computer that knows a *lot* about a particular
domain (i.e. chess), but has no other redeeming features whatsoever. Deep Blue could probably whip 99.9%
of the human population at chess, but it can't even begin recognize the elegance of a particular
strategy (such as the sicilian defense) because it has no ability to make analogies to other domains.
The ongoing thread of Hofstadter's work has always been quite clear. He's interested in understanding
human thought, not mimicking it. In his latest work, Analogies, he and his FARGonaouts (students at his
Fluid Analogies Research Group - FARG) introduce us to several of their long term projects that uncover
some of the 'fundamental mechanisms of thought'.
His usual modus operandi is to examine the problem space of extremely simple microdomains - problem sets having
very few parameters, but that scale up well into higher domains with the analogies it evokes.
For instance, he describes
a very simple game called "TableTop" in which two players face each other across a table in a cafe. On both
sides of the table are arranged various objects of the TableTop domain - knives, spoons, cups, plates, salt
and pepper shakers, etc. The game begins when one player touches an object on their side of the table, saying "Do This", and the
other player then must touch a corresponding object on their side of the table which best mirrors the other person's
The goal in each exchange is to choose the most appropriate corresponding object. Simple, right?
Say I touch the coffee cup sitting in the middle of my placemat. You don't have a coffecup on your side. But you
do have a soup bowl there. You touch it. You've made an analogy. The soup bowl's physical arrangement on the
table was similar to the situation of the coffee cup, and the 'round container-ness' also made it a good match, even
though it was a totally different object. This simple microdomain affords us a lot of insight into the
process of analogy making. That is, the lessons learned in the TableTop domain can be used in other domains
with different details, but similar problem space.
For instance, the Battle-Op Domain, where, two geographical entities are pitted against each other:
(Excerpt from "Analogies")
A war breaks out between California and Indiana over the former's attempt to divert rain clouds from
soggy Indiana to the parched San Joaquin Valley. Unfortunatley, the conflict goes nuclear, and California
obliterates Bloomington. The war council in Indianapolis, wishing to be appropriately punitive but not
risk further escalation, must then decide what Californian entity to annihilate in retaliation. Thus -
what is the Bloomington of California?
Given the act of agression committed by California, it would be nonsense to blast Los Angeles, a city with
a population over 100 times that of Bloomington. Attacking San Diego would be precluded because of its
world-famous zoo. And detonating an H-Bomb in the Pacific so as to cause a tidal wave to destroy Carmel would
be ruled out because an attack mounted on that jewel of a city would likely enrage Californians to a too-risky
degree. After some consideration, then, the war council might reason that the Hoosier Armed Forces would best
achieve 'the same result' not by destroying a city, but by offering all the migrant workers of California one dollar
an hour more to come and work in Indiana.
(Excerpt from "Analogies" ends.)
As you can see, lessons learned about analogy making in one domain can be easily mapped on to other domains of
problems. This is one of the uniquely human attributes of thought - that we can see analogies to things
we've experienced, and use those analogies to help us tackle new problems faced in other domains of life.
When a computer program can be endowed with this ability, then we'll be on the road to artificial intelligence.
The research outlined in Analogies is very intriguing and bucks the status quo in the field of AI at every
turn by focusing tightly upon the goal of understanding rather than mimicking human thought. If you ever find
yourself thinking about thinking - how we think and why we think, then I highly recommend you
pick up a copy of Fluid Concepts and Creative Analogies: Computer Models of the Fundemental Mechanisms of
Thought and curl up by the fireplace with it soon!
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It is a serious attempt to discuss the real issues and difficulties with AI research. There is a lot of quite dry material and in places it is repetitive.
It provides terrific insight into the problem of imitating human thinking at a deep level, and I found it very rewarding. It was also very interesting to follow the threads of how he went about doing research, and what he thought of other AI research.
His views of various flavours of AI research were very instructive and inightful I thought.
In summary a good book, but this is not (high quality) brain candy like Godel Escher Bach etc.
It's great fun reading the book and following the train of thoughts is enjoyable and simple enough ... at least for somebody with a basic understanding in maths and maybe some AI knowledge. So if you started to read Gödel, Escher, Bach: An Eternal Golden Braid but never finished it, this is a much easier and more pragmatic read than Hofstaedter's more generic book.