Artificial Intelligence Books

But the hero seems "ethically challenged"...?
This cyber da Vinci is a software developing genius
but takes a fall at his bosses wishes.
At lot of times Rudy Rucker is on the money in his
futures and he seems in 1994 to see Silly Valley today
better than Steve Jobs does? AI hasn't quite kept up, but
virus technology hasn't made him a liar either.
Rudy Rucker earns his sci fi bucks the hard way.

While most definitely not your garden-variety science fiction, The Hacker and the Ants looks positively pedestrian when compared to some of Rucker's earlier work (e.g. White Light). This is the story of Jerzy Rugby, (a nod to Stephenson's "Hiro Protagonist"?), a computer programmer who has been ruthlessly downtrodden by life. When one of Jerzy's software creations goes horribly (and absurdly) awry, we are swept away in a bizarre plot that offers up intense romance, hideous conspiracy, and a pet robot named Studly. What else could a reader ask for?

Rucker skillfully mixes the real and the surreal, to create an interesting hybrid. The overt and persistent normal-guyness of Jerzy's personality cast against the array of strange happenings adds a nightmarish tint to the story; this is an average man trapped in an increasingly absurd and hallucinatory narrative from which he cannot wake. At points, however, the story goes a little too far over the top (for instance, with names like Jerzy Rugby, Bety Byte, and Krystal Kattle) exposing the seams of the novel.

That is, of course, the ultimate shortcoming (or genius, depending on your point of view) of all of Rudy Rucker's work. Just as obviously, this reminds us that Rucker is not for everyone - for those who are more straightforward thinkers, this sort of style is an acquired taste, at best. But, if you are one of those who enjoy the absurd and at-least-slightly-surreal, I'd recommend the book (and the author) strongly.

In this book, perhaps more than his others, Rudy Rucker takes the common themes of Cyberpunk literature (the frightening/enlightening possibilities of technology) to unique and fascinating ends. For those looking for a taste of just-over-the-horizon technology in an all too familiar environment, you will find much to like here. There is the dependence on visual stimulation and passive entertainment, whose destruction brings about blood-thirsty mobs. There is the shift away from real-world social interaction and towards anonymous techno-societies that makes communication increasing awkward when not accompanied by digital interfaces. Finally there are the ethical and logistical problems involved in giving increasing control and autonomy over the machines that do not necessarily share our moral qualms.

In the end, however, the writing fails to live up to the ideas. The first hundred pages are awkward at times, excruciating at others. Once the meat of the plot begins, the overall writing seems to improve, but the dialog still seems stilted and the pacing is jumpy. Although I had hoped to attribute these factors to the stylistic choices made by many modern sci-fi writers, it became obviously that the writing simply wasn't up to par.

If you want high quality Rucker, you will be better off with his later *ware tetrology.

I'll start by saying what's wrong with this book. Rucker must have had a really bad marriage as he uses his wife in his books rather negatively. But even with this he writes a fantastic book. I can look at the technology that he describes and almost see it in use today. No magic but solid tech. And the story fits so well with the genre of both cyberpunk and today's news. I really wish this book was in print for others to read.

Only four years ago an artificial intelligence engineer and an evolutionary biologist collaborated on a speculation of how computers and humanity will combine, becoming thinking robots. Beyond Humanity:CyberEvolution and Future Minds was met with a fanfare of resounding silence. Well done with strong evidence and good presentation, the book challenged traditional thinking about the separation of machines and humanity. It should have gained greater notice than it did. A pity, for this book should have raised immense discussion.

Now, Rudy Rucker has turned the same ideas into a speculative fiction account of a programmer ['hacker'] using evolutionary processes to make robotic creatures biological. As with all evolutionary processes, his program gets out of hand and the creatures run amok, out of control. Only another robotic biological is capable of dealing with them.

If Rucker ever produced 'his best book' this is the one that qualifies. Many of his other works are loaded with a sloppy kind of mysticism that seems horribly inconsistent with his profession as a mathematics professor. This book seems to merge an audited biology course with his math skills in producing a plausible scenario of the future. That he makes this future so near makes the book even more compelling. Having railed against 'WHITE LIGHT' and SAUCER WISDOM, it was gratifying to find a work of his that tends to redeem his worth as a novelist. The writing, as always, falls below the worth of his concepts. Still the book made an entertaining afternoon. If you haven't the patience or courage to confront BEYOND HUMANITY, you might try this as an introduction to the possibilities of artificial intelligence.

I have to agree with all of johnnied7 criticisms. This book is pitched at a level too advanced for an introduction. It also reads and is structured like a research paper. Not recommended.

I have an engineering degree, and I found this to be a little tough to follow for two reasons:

1. Not enough step by step prodecure especially at the beginning. Mitchell is too quick to start with the math formulas. It turns out that Genetic Algorithms are fairly straight forward and easy to follow, but you have to read this book twice before you "get it" because Mitchell clouds the discussion with proofs and mathematical representations of systems. It is tough to follow.

2. Mitchell does a poor job of selecting meaningful examples to illustrate the points. A nice simple set of examples where the average person easily picture the system would have been delightful. Instead this author chooses to illustrate the Genetic Algorithms through uncommon neural networks amoung other exotic applications. I found myself struggling to understand both the example (I didn't know a thing about neural networks!) and the genetic algorithm.

When buying an Introduction type book, I expected it to be more 'down to earth'. this book is for advanced minds!

This book primarily deals with the theoretical side of genetic algorithms. If you are looking for practical knowledge of how to implement a GA you should look elsewhere. For all intents and purposes this is a textbook. It's heavy on theory and proofs, but doesn't always explain everything in depth (that's what class time is for). There are problems at the end of each chapter that can be assigned to students.

There are case studies of many academic projects that seem to drone on forever and aren't really that useful in helping you learn how to write your own GA. Chapter 1 gives an overview and provides all of the appropriate terminology. Chapter 5 gives an high-level overview of how to implement a GA. Those are the 2 must-read chapters, all of the others can be used as torture for CS students.

To recap, if you're teaching a class in artificial intelligence this book is good. If you're trying to figure out how to implement a GA to solve a practical problem not so good. That evens out to 3 stars for my rating. I recommend searching the web, there are a few good sites on GA programming.

First it must be said that the book is not an introduction that the non-scientist will easily understand. Some knowledge of computer programming is assumed. It acknowledges this in the last paragraph of the preface. Many of the notations in the book are unfamiliar to business or financial readers. There is no mathematics beyond algebra so the aforementioned prerequisites are the main hills to climb.

Mitchell's book is an overview of genetic algorithm analysis techniques as of 1996. The author gives a history of pre-computer evolutionary strategies and a summary of John Holland's pioneering work. A description of the basic terminology is presented and examples of problems solved using a GA (such as the prisoner's dilemma). The second chapter discusses evolving programs in Lisp and cellular automata. Also included in this chapter is a discussion of predicting dynamical systems. This was the section that has the most interest for me. Also interesting was the summary in this chapter about putting GAs into a neural network so that the ANNs could evolve.

The fifth chapter discusses when to employ a GA for maximum success. I appreciate the clearly thought out discussion of when to choose a GA for a problem. Sometimes authors of these types of books mimic the man with a hammer that thinks everything looks like a nail.

This is a great place to start to learn about genetic algorithms. The writing is clear and not bogged down by jargon. The book is not overly technical; it is written for the layman and has a casual conversational style that is a pleasure to read.

About half of the book is devoted to presenting examples of studies that have used genetic algorithms. These examples are interesting in themselves and also serve to illustrate the variety of genetic approaches that are available. The book also presents conflicting points of view of experts about which algorithms work best and why. This is helpful in combatting the impression that a beginner sometimes gets that everything is simple and all the answers are known.

This book was purchased for a university course.

It appears that the charts, tables and graphical headings were in colour at some stage, but this edition/printing is all in black and white. The result is black text on dark grey background on all the charts and tables.

Rather unpleasant.

For the people who is involved with KM, you may have read a lot of information about it. KM is a complex and theoretical topic, with a lot of theory. This book takes yoy step by step, since conceps to implementation, helping you with a KM CD that has usefull tools for the KM practice.

Luis Iván de la Fuente

Most texts on knowledge management are strictly theory. This is one of the few that I have seen that has taken a "hands on" approach to KM. Certainly a lofty goal, and the author does a good job trying to reach it, but still falls somewhat short.

The diagrams, checklists, and templates are thought-provoking, and will help you design YOUR KM program. Full lifecycle, thorough, and plenty of case studies. Overall, I'm quite pleased with its content.

One will almost immediately notice the research and writing style--the author is obviously from the academic world.

This is a book that makes a good balance between theory and practice. It presents a complete step by step guide to implement KM in your organization.

I recommend it for people who are in charge of a Knowledge Management Project or defining a KM strategy for their organizations. Is not an only "theory" book like most text or articles on knowledge management.

Illustrative book with templates, checklists that can help you organize your KM project.

Cesar Castillo

This book is a poor application of the KM subject. It has non-sensical terms like "knowledge management server" that would only make sense to a Boeing engineer...

This volume is a bit boring compared to the other volumes. No central struggle or triumph, just a series of minor adventures capped by a big birthday party. There are some decent lessons for children along the way, chiefly the perspective of beauty (in the eye of the beholder, of course), and a slightly more subtle example of love versus truth (one of the characters is 'truly' loved at the end, but only after he tells the truth and abandons the 'false' love of his charm).

The book appears to lose its narrative steam relatively quickly. The first few chapters have a traditional fairy-tale quality to the writing, but that fades after 3-4 chapters. The chapters in Foxville and Dunkiton have an interesting narrative thread (each society thinks itself the brightest and transforms the character conforming to their preconceptions of intelligence), but it stops by the time the group reaches the Musicker. After that point in time, few other themes emerge and Baum appears to be piecing one tiny adventure after another simply for the sake of getting to a birthday party.

One final note, maybe a bit over-thought for a children's tale. It seems as if all of Ozma's friends were made on adventures. Thus, the true inner circle at court is decided by merit rather than by nobility (all the 'nobles' are secondary characters at best during the birthday party). This is a good message for children, but it begs the question - will Oz be subject to entropy? As Ozma's adventures outside the palace slow down and friends slowly slip away, does the royal court revert back to nobility-based preference? As I mentioned, maybe this is over thinking it a bit

I've been a fan of Frank Baum since I saw the MGM film The Wizard of Oz; I remember watching both the original film and the version with Japanese voice-overs (and if that's not hardcore, I don't know what is).
The Road to Oz was the beginning of a collection for me. I recommend it to those who truly loved Baum's creation, his wonder-world. There are new characters introduced in this book as well as old veterans (the Scarecrow and Tin Man are still present). Not quite the classic and nothing too terribly outstanding about it, The Road to Oz is still an entertaining fantasy story.

Read this book it is the best! I read like two chapters a night I liked it so much. It is full of adventures. It is very cool! Anyone should read it. The book is axesome! So READ IT!!!

L. Frank Baum returns to Oz with a splash in this book, inviting Oz fans to the royal birthday party of Ozma and treating them to a "who's who" in the world of faerie--why even old Santa Claus makes an appearance! As a child, I was just pleased to have Toto back in Oz (his first return since "The Wonderful Wizard of Oz"), and one of my favorite illustrations in the whole book shows the little black fellow getting a friendly pat on the head from the Cowardly Lion as the two old friends reunite. There are some new characters in this book of course, including the delightful trio of Button Bright, Polychrome, and the Shaggy Man. I'm inclined to think that these were three of Baum's favorites, for while he often created characters that never made significant appearances in later books (Eureka the kitten, Billina the hen, Woot the Wanderer, etc), these three all played leading roles in future Oz installments. Character is definitely the focus in this book, and like much of Baum's work, "The Road to Oz" does not have a definite plot. Still, for any fan of Oz, it provides such wonderful escape that this party is one that you won't want to miss. The illustrations in "The Road to Oz" demonstrate the talents of John R. Neill at their peek, and this edition of the book is printed on colored pages to mirror the rainbow shades of the Land of Oz--at first this ploy seems a bit distracting, but by the end of the book one realizes that Oz is just that colorful.

As noted by some other reviewers Road to Oz doesn't conform to the usual requirements of a fairy tale such as a quest or continual action adventure. However, I believe Baum was aiming at something different here, namely, evoking the wonder, anticipation and shared excitement that young children feel at a birthday party (the point of the book is the celebration of Ozma's birthday). The first edition of the book was even printed with paper of different colors like the colored paper used for decorations. In these terms, Road to Oz is perhaps one of the best written of the Oz series with very few false notes or awkward characters. The characters of Button Bright, Polychrome, the Shaggy Man and Johnny DoIt are particularly good. Actually there is a quite a bit of action and adventure before Dorothy and her companions arrive in Oz. The transformations of Button-Bright and the Shaggy Man into fox and donkey respectively, while straight out of Classical myth, have an unusual twist: their motivation stems not from malice or the Gods' sport, but rather from the transformer's inability of seeing more than one standard of beauty. Once in Oz, Baum handles the pageantry and socializing in deft fashion for a children's story. In short, an essential part of the Oz series.

Book needs some more content, it gives a good first level intro but does not develop it into more interesting/advanced things.

50% of the book is a 'sales' pitch for StarLogo.

If you have experience with writing code for simulations this book is a bit light technically.

Still has some interesting ideas in it.

On the surface, the book seems focused on computers and even video games. This makes the activities appealing for middle and high school students. However, the ideas in this book are actually relevant to two entirely different fields: 1) genetics, and 2) artificial intelligence. Both these fields have at their centers the concept of complexity arising out of simplicity. Students who work their way though the activites in this book will find that Dr. Resnick offers a window into a deep mathematical world that has applications far beyond computers and games.

Mitchel Resnick shares a lovely sense of wonder, discovery and fascination in this slim, easily read volume about agent based modelling. Using micro-worlds (termites, ants and other modelling metaphors) Resnick shows us how collective behaviours are more than a simple sum of the parts - and through his experiments using StarLogo programming he shows the nature of emergent behaviours that come through decentralised thinking.

His reading list is a great starting point for anyone fascinated by Complexity and Agent Based Modelling, and so too is his elegant list of guiding heuristics that he has learned through toying with various ants, termites, forest fires and traffic jams.

- Positive feedback (in models) often plays a vital role.
- Randomness can help create order. Random isn't always chaotic.
- A Flock is not a big bird. The behaviour of groups should not be confused with the behaviour of individuals.
- A traffic jam is not just a collection of cars. Emergent objects have an ever-changing composition.
- The hills are alive. Don't just focus on the individual objects - look also at their environment.

This volume helped our research team design approach agent-based modelling, and put us in touch with other avenues of decentralised thinking: for example Network Theory. Best of all, Resnick helped us lighten-up. This book (and its subject matter) has profound ideas, but never loses a delicious sense of awe. Recommended.

This book provided the motivating force to write my first, and last, review for Amazon.com.

Over the past 5 years since my first reading Mitchel Resnick's Turtles Turmites and Traffic Jams, the book has come up on numerous occasions related to several topics, two of which most basically:

1) Writing style - Resnick's clear, well-researched, simple yet profound style. His background as journalist and inventor enables TT&T to walk a new line between source material and criticism.

2) Content - Resnick's theoretical application of emergent behavior to education is robust; his practical educational tools (starlogo and later, mindstorms) are a fundamentally clear and wondrous collapsing of idea into artifact.

I will include this book with few others in my life bibliography.

This is a book describing the research of a team at MIT using a version of the educational language "Logo". Running in a simple graphical environment which supports multiple parallel operation of code in the same shared space. Write a few lines of code for an "ant", then let 1000 of them loose. The current version of this "StarLogo" system is written in Java, and available as a free download for anyone to play with.

The use of Logo is both a strength and a weakness of the approach. The strength is that the code is concise and easy to understand. The weakness is that there is only one source of the software, and anyone wishing to try it is limited to the available download. This would not be such a limitation if the book described the same version, but unfortunately things have moved on a lot since the book was written, and few (if any) of the examples will work without alteration.

As well as the development of the StarLogo system, the book covers experiments in emergent behaviour. Typical sections include how parameter and environment changes can affect the growth and development of simulated ant colonies, and a theoretical basis for those "phantom traffic jams" we have all experienced.

This book is certainly interesting if you are interested in developing parallel software simulations, or if you are interested in marginal computer languages, but don't expect the code to work without effort.

Hofstadter provides effectively a series of articles published elsewhere, edited in his engaging, verbose style.
Basically the question of the book how would a computer solve the following:
"X:x as Y:?"
You can get much more complex, but basically his group spents the 80's and early 90's researching this questions and trying to figure out, "know when to break the rules" applied.

His overall appraisal of AI is that even within confined realms, it still produces inconsistent results, and there is a long way to go.

Processing power is ~1000x greater than when he wrote this book, but as he observed with Deep Blue, "Brute force methods tell us nothing about Human thought".

I realized this was a small sampling of the issues facing the whole approach. Enjoy.

When I first starting reading "Fluid Concepts" I found myself puzzled; what, exactly, was Hofstader up to? He and his team of grad studenst seemed to be spending a tremendous amount of time on something that at first struck me as very trivial- solving puzzles of the "what number comes next" variety. I didn't see the connection to cognition. I put the book down for a while.

When I returned to it, after having done some refresher reading in cognitive psychology, Hofstaders' intent was much clearer. To understand his program, you have to start by discarding GOFAI ideas about the stored representation being primary, and look at the problem as a psychologist would: Before you can even ask how representations are stored, you have to ask how they got there in the first place, and that's what Hofsatder is looking at here.

Perception consists in large part of taking a mass of sensory data, and looking for patterns- in it. That's a critical part of cognition. It's both how we extract words from marks on paper or sounds uttered by another, and why we see a face when we look at a full moon, or a stain on a curtain, or a piece of burned toast. Hofstader and his team are looking for those fundamental processes that allow to both match raw perceptual data to representation, and to generate those representations in the first place.

Since the publication of this book he's moved on to another research program, and having been away from the field for over a decade, I'm not sure how influential it has been. But as far as I can tell, no one else has done as in-depth an analysis of this sort of primitive pattern matching, and for that reason alone, I think it's a program that every cognitive scientist should familiarize themselves with to some degree.

I read this book when it first came out. At the time I had a deep interest in all things AI. The book presents Dr. Hofstadter's experiences (along with those of his graduate students) of implementing creativity modeling systems (and others) at the Fluid Analogies Research Group (FARG). The book is not an easy read. The reader will need to be diligent and not get deterred. The book also is a bit dry in areas, but those who are truly interested in the subject matter will not mind, much.

This book is, as others have commented, different from DH's other more entertaining books.

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.

Many books by D. Hofstadter are at the top standings of my personal parade, but in reading this book I found myself very likely too distant from my usual interests and preferred styles. The initial part is very interesting, but when the author carries on detailed descriptions about programs' features in conversational shape, I have been quickly bored, and I have given up attentive reading turning to an eagle eye approach. I would have been by far more comfortable with a more formal explanation, because, once I make the effort to follow the thourough description of what and how a program does, it is more convenient to study its algorithms.
So, the book is surely very pleasing for people professionally involved in semantics, but I am not confident in its general interest.

Brilliant! The fantastic murderous android from "Gridlinked" returns amidst shadows of mystery and splashes of blood. Asher is as on form as ever with his to-the-point, indomitable style as he resurrects the fan favourite.

Thankfully this isn't just a piece of mindless action for the fans, like many cash-in sequels. It is a well thought out thriller constructed around the resurgence of an ancient technology, a feature of Asher's Polity world that has been hinted at earlier in the series. Here we see a step away from technological threats toward organic threats, and interesting change in direction for the series that keeps things fresh. The characters have yet to become stale after three novels, particularly the dracomen and the massive, Delphic entity Dragon itself.

Frustratingly, the most mysterious character of the series remains a flat non-entity; Horace Blegg, who is deliberately kept as an enigma, features more as an annoyance now than an intriguing sub-plot. Presumably Asher caught on to this as the fourth book "Polity Agent" finally provides us with some answers to this flagging mystery. Similarly there are problems with additional characters added to the mix, such as the "knight" who is searching for his figurative dragon, who ultimately has little impact on the story. No doubt Asher will tie up this loose end in later novels, but it remains neglected entirely from the fourth book and the character seemed to have little, if nothing at all to do with the overall storyline.

These are small issues though, and the overall enjoyment of the book is left mostly unspoiled. Overall it's another wonderful and entertaining deep-space yarn that had me at least ordering the sequel before I'd even finished it ... 3.5 stars, but since I'm not allowed half measures I'll bump it up to a respectible 4!

Super agent vs super criminal, again.


When you do the super secret agent in space type of story, it is generally important to have more of a personal focus on your hero. This book, at least in this incarnation is around 500 pages long, and a lot of the middle is taken up with other threads, that while tangentially interesting are nowhere near as good as the parts featuring Cormac and his directly related allies themselves.

This includes the locals on the planet, the dragon slayer quest, etc.


The part that does work as well as that is when the viewpoint steps back even further, to the conflict between the various AI entities, and hints at their plans and goals, sort of a cross between Culture Mind ships and the Technocore in Hyperion, to a certain extent.

Asher could have chopped a chunk of this out and made it a better book for keeping the reader's interest -the dragon hunter story may well have made a good stand alone novella.

Editorial demands to be this length? Who knows, but the middle of the book was certainly tedious, at times.

The same cannot be said for the start and the end, which were definite improvements.

Padding is not a virute in this sort of bloody superhero space opera, in general.

The title character, referring to the android Mr. Crane, is again not much of a feature, except for a mysterious revelation near the end - which presumably might leave him starring in his own story, later on.


3.5 out of 5

I'm now on Polity Agent, having read the first three books in the Ian Cormac series. Brass Man is the third (of four) books in the series, and another excellent addition. Reviving Mr Crane, the psychotic Golem from Gridlinked, Asher pits bad guys with nano-infused, alien technology against our series heroes in the usual hostile environment of leviathan monsters and AI-led ships racing through u-space overhead. Enjoyable for its dense plotting, imaginative flora & fauna, and action. I've mentally screened it as the last Bond melded with the first Star Wars, throttled up to Tarantino ultraviolence levels.

At times it was slow going because characters fleshed out in previous novels of the series are introduced here with no explanation. However, I thought it was an excellent sci fi read, up there with novels like Starship Troopers, Ender's Game, Forever War, et. all. Tons of stuff going on, great prose style, very cool characters and engrossing good v evil plot. Highly recomended.

+1 for bone-crunching non-stop airport loung action
+1 for sizzling wit - especially the Cervantes characters
+1 for total mastery of his plot-line and weaving it all together
+1 for bettering Ian M Banks, Peter F Hamilton and Alastair Reynolds

-1 to the publisher for NOT making clear on sleeve this was #3 in series

Bottom line: best thing to happen to Brit SciFi in light years! B

This is a speculative science writing of the best quality. This discusses the issues of machine intelligence among five seminal thinkers as they talk to each other at a Cambridge university dinner party. A primer reading on machine intelligence.

This is a story of a meeting that took place, but actually could not. It is about 5 people who met for diner who talk about the topic of Artificial intelligence. Throughout this meeting, the 5 intellects argue over what would occur if machines really could think on their own. The book takes you into the beginning of the Computer Science era. It speaks of algorithms. Overall, the book is about the artificial intelligence and what is to come if it is to become a reality

The reading is alittle sluggish at times, but interesting to those who are fascinated with things ilke this.

I confess a weakness for this kind of format, a fictional situation in which historical figures meet around a table and argue their various points of view face-to face. This short book is an especially nice example of the genre, with the protagonists meeting around the dinner table in Cambridge on a stormy English night in 1949. It recalls a certain variety of detective story, and in a way that's what it is. But the essential mystery, what it means to be a thinking human being, is not finally solved.

Many of the key issues connected with language, thought, and the possibilities for machine intelligence are touched on in these conversations, giving the reader a good sense of the kinds of philosophical and technical questions that remain unresolved even today. The mode of presentation is probably about as entertaining a one as possible for an introduction to this kind of material. At a minimum, I think your reaction to the book will tell you whether you have enough interest in the subject matter to pursue it much further. But even if you don't, you will have encountered a great many stimulating ideas in these pages. And you will know enough not to have to sit there like a stupid lump should the subject of AI (Artificial Intelligence) come up in conversation. The book does not go as far as some reviewers would have liked, but I think it nicely does the introductory overview job it set out to do.

My only quibble is that while Chomsky's later ideas about language are presented (Casti admits the anachronism as a way to get certain ideas into the conversation), behavioral psychology is not given the benefit of a similar updating. Skinner's work on verbal behavior was quite sophisticated, much akin to the view here put forth by Wittgenstein, and far from the old Watsonian stimulus-response version of behaviorism used as a foil in the book. That was a difference, by the way, that Chomsky never managed to comprehend.

In this book, John Casti, who in my opinion may well turn out to be one of the foremost science writers of all time, weaves a tale about an extraordinary meeting...that never took place, but could well have. Five outstanding intellectuals-C.P.Snow: Physicist, Erwin Schrodinger: Physicist, J B S Haldane: Biologist, Ludwig Wittgenstein: Philosopher and Alan Turing: Mathematician-meet for dinner at Cambridge University's Christ College in Snow's rooms, at his request, for profound discussion about a topic that could change the future of humanity forever. The topic: Artificial Intelligence. Can machines think? During the intense discussion that follows, we get to read about a tour de force presented by Casti, just like it would be, had such a meeting actually taken place. As these great minds argue back and forth about this central question, we are transformed to post war England, and the beginnings of modern day computer science. Almost everything they talk about had, or will have far reaching consequences. Some of the idea Turing talks about, such as algorithms, are so commonplace in the modern world, that we take them absolutely for granted. Other related questions, such as the origin and structure of language and its relation to computational processes, are still profound unsolved questions. Casti makes everything sound extremely realistic, and does a great job at it. His choice of characters for this debate is superb, and one which cannot easily be imagined, but which in hindsight is perfect. His portraying of their personalities is impeccable, and represents the diverse backgrounds which each of them brings to the dinner table. His language is brilliant,and so is the humour.
What about the conclusion? There can be none for such a complex problem. But the knowledge which one gains in such enterprises is priceless. Forget about Bill Gates, George Bush, and Saddam Hussein (although they DO make a difference!). Gentlemen such as these are the real movers and shakers of the world, although few may hear of them ,for they toil as little known geniuses. We should be indebted to writers like John Casti, for telling us their story. Thank you, John!

This venture into the murky waters of historical speculation and machine-consciousness debates does tell you a few things if you are unfamiliar with Turing and Wittgenstein (otherwise, don't bother reading it). But while Turing's viewpoint is clearly stated from the start, Wittgenstein's is only done justice at the end. The other three characters in the book could be merged into a single one without any loss, and in general the entire book's message could be condensed in a few pages. Which would be pages worth reading if you like articles in easy-reading popular science magazines (which I have nothing against, and indeed subscribe to).

This is a pioneering book dealing exhaustively with the subject of causation. Its contribution to the field of "Uncertainty in AI" is unmeasureable. It dealt with graphical models for reasoning in depth. For computer scientists looking for an encyclopedia of algorithms and applications on causation, there can not be a better book. I highly recommend this book for researchers in UAI. A word of caution: This is not a book for starters and those who do not have a well developed concept of uncertainty.

The scientific research community has adopted rigorous methods to eliminate the need for subjective judgments about many things, but when it comes to testing whether X causes Y, they revert to intuition and hand-waving. This book makes a strong argument that we shouldn't accept that. It demonstrates that it is possible to turn intuitions about causation into hypotheses that are unambiguous and testable.
But the style is sufficiently dense and dry we will need some additional books with more practical styles before these ideas become widely understood. The style is fairly good by the standards of books whose main goal is rigorous proof, but it's still hard work to learn a large number of new concepts that are mostly referred to by terse symbols whose meaning can't be found via a glossary or index. Pearl occasionally introduces a memorable word, such as do(x), the way a software engineer who wants readable code would, but mostly sticks to single-character symbols that seem unreasonably hard (at least for us programmers who are used to descriptive names) to remember.
If you're uncertain whether reading this book is worth the effort, I strongly recommend reading the afterword first. It ought to have been used as the introduction, and without it many readers will be left wondering why they should believe they will be rewarded for slogging through so much dry material.

Pearl included an Epilogue containing a lecture he gave in 1996 entitled, "The Art and Science of Cause and Effect."
Pearl concludes the lecture by comparing his theory of causality to the first mathematical tool,the abacus: "But the really challenging problems are still ahead: We still do not have a causal understanding of poverty and cancer and intolerance, and only the accumulation of data and the insight of great minds will eventually lead to such understanding. "The data is all over the place, the insight is yours, and now an abacus is at your disposal, too. I hope the combination amplifies each of these components."

Unfortunately, virtually no advances have been made in learning the causation of intolerance nor how to rid us of it. And Judea Pearl suffered immensely because of that . . . Daniel Pearl, his son, was killed in Iraq due to intolerance. :-(

BTW, the book is great.

Judea Pearl is one of the leading researchers in the topic of casuality. What is causality? In the exploration of statistical data we are often able to find relationships or correlations between two variables. We are often tempted to attribute the results of one variable, say A as an outcome (being high or low)that is due to the result (high or low) of the other, say B. We want to say that B is the cause of the outcome of A. Significant correlation by itself only suggests relationships. It cannot tell you whether A causes B or B causes A or neither. Causility is the study of designing experiments to allow you to determine if a relationship has a cause and effect. The subject matter is very philosophical and somewhat controversial. But a lot of research effort has gone into providing mathematical rigor to the concept. Pearl is one of those rare scientists who can contribute to such theory and explain it. But as Aickin suggests in his amazon review this is not a subject for a novice. Previous exposure to statistical methods such as correlation and regression is imprtant to a clear unbderstanding of this book.

This is a very interesing book that Judea Pearl worte. The topic is currently of general interest for diverse fields as economics, social sciences and biology, however, this book is not intended for practitoners from these field who face a special problem and search for a possible solution. If you want to buy this book for this reason you will not be able to extract this information for this book. The reason therefor is that important technics like Bayesian Networks or Structural Equations are treated in 3 pages in each case. Judea Pearl assumes that the reader is already familiar with such methods beforehand. (Readers interested in the later subject are strongly refered to Bollen's book "Structural Equations with latent variables".)

Moreover, I do not think that this book presents state of the art information about our current knowledge of this subject. For example, the important problem to extract a network structure (structure learning) from data rather than estimating the parameters of a given networks structure is completely missing.

Nevertheless, this is a good book, because it might give you in the long run (you can not read it in one piece) insights you did not have before. Of course not to all topics causality is involved (see, e.g., above) but the given topics are thorough explained albeit on an advanced level.

Update: I add one star (total three) to my evaluation, because in the meanwhile I appreciate the historical development described in the book including references to the literature.

This book gives a very deep insight in the problems of the creation of systems with some intelligence.

I seldom pan books, but this one is little more than an egotistic rehash of simplified versions of AI/AL theories of the past 3 decades. The only new data are the author's opinions. If you are looking for anything new and/or in depth, look elsewhere.

There are some interesting analogies and examples of perceived or emergent behaviour but overall many of the arguments do not hold up to scrutiny. If you are looking for a book written in the form of opinions, as opposed to hard facts, then this book will be more to your liking. Certainly something I would borrow from a friend/library rather than paying for it to sit on my shelf - not something I will go back to in future to read again or for reference. It was a disappointment as I was led to it from Richard Dawkins' excellent "The God Delusion".

I must say I enjoyed the book completely. While I don't agree with the author on all points - the book is incredibly though provoking. I was so glad to see such a book written that after I read the book (in 3 nights - short book) I bought three copies for co-workers who I wanted to read it. Steve Grand is now quite famous (or should I say even more famous) after writing this book. He has challenged traditional thought on the subject of AI and in a way made converts out of many.

However, he spends 10 chapters saying "you are all wrong - this is the way to do it" - then doesn't follow up on doing it himself but rather takes enough shortcuts to make the work suspect - but to his credit he does say he's doing going just that :) All in all - if you're a software engineer or software developer I highly recommended the book.

Grand's book isn't that at all, although it tries to be. He starts out with his definition of life, and builds (slowly, oh so slowly you could cry) up to the point where the rubber hits the road, so to speak. At that point, he imply handwaves the entire process of programming a-life.

So in short, there are books out there that do a better job of explaining the application of neural networks. There are better books on the philosophy of consciousness and life. There are better books on game design.

So you don't need this one, because Grand only tells you what you already know, if you're at all interested in the subject, and doesn't add enough best-practice techniques to make his way of building a-life better than any other. It's as though he was so worried about giving away his secrets that he redacted all of the information in the book that would have made it more than 'Here's my philosophy.'

The only thing saving the book from a one-star review is that the first 10 chapters do light a fire in your belly to find out more. But this book isn't going to provide that 'more' that you want to know.