Artificial Intelligence Books

Rodney, neuroscience explorer, returns from a trek into the unknown chart area, "terra incognita". Consciousness and mind hide there and now this book yields up their secrets and treasures. Well illustrated, apt quotations, written with beautiful expression and constantly rigorous in thought and argument. Science writing now days divides into the noisy and the hidden gems. The first is smart agents, pushy PR and personalities that constantly self promotion but write work that never lives up to its flash and advertising. Would that Pinker was as good as the ads tell us he is. In the second group are those that never get into the stream of success because they are too good natured for the game. But they write the science that is worth reading. Professor Cotterill - at least after reading this book -- is at the top of that group. Having read Pinker's Blank Slate, I wished I had read this first - better is a personal judgment but this is. Not a book for indenting from the library but buying for a holiday and pleasure.

This is vastly better than the meretricious commercial books that clutter up this area. Cotterill is (a) well-informed; (b) writes compellingly and clearly, with analogies and new ideas that will make even neuroscience professionals sit up and take notice. It is emphatically not just another piece of popularisation.

This is an extremely comprehensive book. It covers many aspects of neuroscience and neural networks. Among a lot of information, there is his theory of consciousness. He bases his view of the mind as action centered, and this is to my mind, a good move. It is no surprising that his model includes sensimotor areas. He also includes the prefrontal, premotor, and the thalamus intralaminar nuclei, forming a loop, in his theory of consciousness. He supports it quite well, and it gives rise to predictions that can be experimentaly tested. The data considered is overwhelming, so even if the consciousness theory end up not being totally right, the book as a whole is still a very important piece of literature in the neurosciences. Qualia as essentialy the effects of muscle-spindles in the loop at first seems confusing, if not implausible, but maybe deserves further consideration. Not a lot of neural network talk, but enough to complement nicely.

Daniel Dennett doesn't Explain Consciousness and Steven Pinker doesn't really tell us How the Brain Works. Cotterill does both: at a level of detail which allows the expert (which I am not) to evaluate his claims, yet in a style which is always accessible to the scientifically aware general reader. The evidence, getting down to the individual neuron and its dendrites, builds up to an overall picture which shows consciousness to be the outcome of a sort of time-lapse pattern matching process in the brain. This book really tells you how it works: it's not just a bunch of philosophising -- it's all (almost all, 'cos he does allow himself a speculation or two) based on experiment. Cotterill concludes by telling us that he and his students are now working on computer neural networks which should result in a computer which (convincingly) simulates consciousness. [Maybe I shouldn't have given away the ending.]

If you are, like me, an "amateur" when it comes to the study of the mind, you have probably sought to balance your reading of philosophers like Dennett with something more solid from the science of mind. "Enchanted Looms" is a fine place to do that.

This is not a book to sweep through in a few days. You will want to pause and digest. Although Cotterill is clearly aiming at an educated layperson as a reader, he bows, stylistically, to an academic audience. This interfered with my reading of the book. Dozens of times per chapter, he cites sources parenthetically or within the text. Too many sentences begin in the form "The work of _x_ and _y_ has shown..." For the longest time I kept thinking that noting and remembering those names would help me in following a line of argument. This was rarely the case. But then, at times, a backward reference to "_x_" would stump me. Once I learned to glide over these I found it much easier to read the book.

The tie-in with "neural networks" was an interesting process since I had little sense of their importance in cognitive science. Cotterill does a nice job, initially, of showing how such structures might work in both the abstract and at the level of neural anatomy. But, interestingly, he moves on to make a convincing case that such structures cannot adequately model all the functionality of the human brain. I came away from this book with the sense that neural nets are the "Ptolemaic epicycles" of brain science - a paradigm that with growing complexity and constant tweaking can just barely model what we know about a physical phenomenon, but which are not up to the ultimate task.

Cotterill does a nice job of making the macro-anatomy of the brain a part of a meaningful whole. Too many neuro-anatomy-focused books seem to just carve out the various regions and leave a sense of oddly unconnected "vision centers" and "speech centers." "Enchanted Looms" presents much more of the sense of the interconnectedness of those zones that we have chosen to isolate as anatomical pieces. He goes into some depth about how these connections might themselves function as a layer in the processing that we call thinking or sensation, ... or consciousness.

Which brings me, in the end, to the grail in my own "brain-book" search - "consciousness." Sure its fascinating to realize how interesting the study of, for instance, vision, might be, but its that "me" in there, in HERE, that wants some explaining. Although this is not the focus of Cotterill's book, he does propose a very different model for consciousness from any that I have seen - seemingly centered around neuro-motor systems; an odd twist on the notion of a "muscle-head" ! I say "seemingly" because it was really only upon reading this concluding section of the book that I realized I might not have understood enough of the prior 500 pages. Cotterill's argument for this unusual underpinning of consciousness seemed somewhat unconvincing, to me, only to the degree that it built upon elements of his model for brain that I had only partially grasped.

So I will reread this book... a very unusual thing for me, for this topic. It bespeaks the power of the ideas it presents that I know "Enchanted Looms" will be worth that second effort.

This book covers a lot of ground -- check out the table of contents and you'll see something for every flavor of computer or video game, from the Atari VCS to PC-based first-person-shooters and massively multiplayer online role-playing games, to handhelds like Palm and Pocket PC devices, to all of the major console machines you attach to your television.

Like any computer book, this is full of ephemeral information that may not age well. In a few years, many of the links given here will cease to exist, and much of the hardware referenced could be difficult to find. Some of the tools which seem cool today will be commonplace, having been built into new revisions of hardware. The author does a good job of anticipating where this might happen, and sticks to generalities while providing specific examples wherever possible. As I write this review, the book has been in print for almost a year, and in my opinion, it remains fresh, relevant, and worthy of purchase.

Some of the activity described in this book is in the grey area between legal and illegal activity, and Carless takes care to warn the reader when he/she might be stepping on dangerous ground. Such caveats make this book even more interesting to this reviewer and probably others as well.

If you've ever done any of these things, enjoyed it, and wanted to do more, then this book is for you!
- played a Japanese game on a USA or UK territory console;
- played a "hacked" ROM of an old game in emulation;
- wanted to get more out of old games which are boring now;
- wondered about nonstandard import adapters and accessories;
- wanted to interface your console with your PC

In other words, if you're creative enough to want to think outside the narrow box that some manufacturers have put us in, and want more, you want this book, even if you've already done a lot of this stuff on your own. The weblinks alone will provide hours of entertainment, but the book draws everything together into a coherent whole. Cheers to Carless for writing this and to O'Reilly for having the courage to publish this in the age of the Digital Millenium Copyright Act!

This book was a lot of fun to read and provides a lot of great tips for not only getting the most out of your current gaming system, but also for enjoying those games you played 20 years ago. The book starts out with an introduction to emulation and MAME, which allows you to play old console games (like the Atari 2600) or arcade games on a PC. The author even provides directions to illustrate how you can take an old Atari 2600 paddle controller and hook it into your PC (with a soddering iron and a little work). Any gamer who ever played on the Atari would love something like this.

In my favorite chapter, the author shows how to maximize portable devices for gaming fun. In one hack, the author shows how to play games on your iPod. In another hack, the author shows how to produce color pictures from the Game Boy's black and white camera attachment. There are even instructions for turning your PocketPC or PalmPilot into a Game Boy or even a Commordore 64.

The author has a section dedicated to creating the best game machine, where he discusses video cards, mice, and other peripherals. In other sections, the author discusses how to modify your gaming console, including Xbox mods, tunneling (e.g. making games play online that weren't designed to be played online), and other game hacks. Finally, the author rounds out the discussion by demonstrating how to create and add a vehicle to Unreal Tournament 2004. While it does require a bit of time and some work, I was surprised at how relatively easy the whole process was.

This is a great book to read if you enjoy gaming-regardless of whether they're games from 20 years ago or brand new. This book will help you to get the most out of your gaming experience and have a lot of fun doing it.

If you want to go far beyond the obvious, whether you want to modify your console controller to work on other consoles, create your own text adventure, or modify your Game Boy, there is an awful lot of fun you can have for cheap or free, using the creative exploits of the gaming gurus. Gaming Hacks is the indispensable guide to cool things gamers can do to create, modify, and hack videogame hardware and software.

Everything from social exploits and tips to be used in MMORPGs (Massive Multiplayer Online Role Playing Games) to soldering-iron heavy hardware hacks is covered in this extreme-cool hack guide written by gamers for gamers. Gaming Hacks offers a stunning variety of hacks, exploits, and other creative acts on both modern and archaic console hardware and today's PC hardware. One hundred detailed, ingenious hacks are included.

Gaming Hacks also includes detailed software-based looks at MMO (massively multiplayer) titles, FPS (first-person shooter) games, machinima (real-time movies created using game engines), emulation, save-game hacking, and many other miscellaneous subgenres and topics.

Gaming Hacks shows hardcore gamers how to configure the best FPS peripherals, hack the Nuon DVD Player/Gaming System, modify their Game Boy, watch movies and listen to music and their Sega Dreamcast, and much, much more.

Gaming Hacks shows you how to do things you didn't know could be done. If you want more than your average gamer, if you want to explore and experiment, unearth shortcuts, or make your games do what you want them to do Gaming Hacks will show you how. You don't need to be gaming guru to pick up Gaming Hacks, but you will be one when you put it down.

This book covers everything. You can go old school and get information on Mame games and building your own arcade machine. It covers portable with information on PDA games, hacking your Gameboy, and installing a PS2 in your car. It talks about the online world with combat strategies, how to game the systems to make money, and how to find and avoid cheaters. It's got great advice on how to build high end gaming PCs. Consoles are covered as well. He talks about overclocking them and chipping them to play import games. And that's just a sample.

Were this any other type of book I would say that the coverage is unfocused because it's too broad. But it's a Hacks book and these are intended for people with a clue to give them material on a wider range of topics. It starts you off and expects that you will run with it. For example, you get a lot of information about how to create a home arcade machine with Mame, but you won't get the detailed construction plans.

The text is well written, though he does tend to use the gamer lingo, so you may need a translator if you aren't up to the minute. Certainly the best book I have seen for people who want to push their gaming experience beyond what you can get out of the box from Electronics Boutique.

If you're a gamer who is always looking for new information to improve your gaming experience, check out Gaming Hacks by Simon Carless (O'Reilly).

Chapter list: Playing Classic Games; Playing Portably; Playing Well With Others; Playing With Hardware; Playing with Console and Arcade Hardware; Playing Around the Game Engine; Playing Your Own Games; Playing Everything Else; Index

Like all Hacks titles, there are 100 hints, tips, and hacks that cover the spectrum of gaming, from hardware to software, from consoles to online gaming. If you're old like me, you might enjoy Play Commodore 64 Games Without the C-64 (#2) and Play Atari ROMs Without the Atari (#3). Those will take you back to your early days of computing. If you're into first player shooting games, Tweak Your Tactics for FPS Glory (#94) will help boost your scoring. Carless will even help you play Japanese video games without knowing the language in #97 - Play Japanese Games Without Speaking Japanese. He shows you some basic hiragana and katakana that you'll encounter frequently in those games, and that might allow you to bridge the language gap.

The only trouble I see with the book is that it's covering such a wide area of subject matter. Unless you're a full-time gamer, you'll probably find a number of areas in this book that don't pertain to your interests. In some ways, that's OK for a Hacks title, as not everything is meant to apply to every single reader. But this particular title seems to be a bit more scattered than usual. The material is good, to be sure, but each reader may have a different opinion of the book based on what their gaming interests are.

The articles in this work are written by a who's who list of authors from the cognitive and computational neuroscience community. Each article is useful for getting an initial bearing on a topic from this dynamic field. The references for each article serve as useful "jumping off points" for further learning. It should be noted that this text is not a typical college textbook -- it is a reference work. As such, a beginner to the field should consider one of the other introductory textbooks (perhaps "The Cognitive Neurosciences").

Review of Second Edition (January 2008):

This sizable collection of articles updates the first volume with many discoveries and conceptual developments that were unknown at the time. Meant of course for reference, a typical reader, such as this reviewer, would probably not read every article in the collection but would instead concentrate on the ones of primary interest. The editor however does offer advice on "how to use this book" at the beginning of the book, for those readers who intend to use it as their primary source of information, or for instructors who will use it as a supplement to such classes as brain theory, artificial intelligence, computational neuroscience, and cognitive neuroscience. All of these topics are represented, with emphasis of course on those that the editor finds important. Time constraints will of course play in role in any sampling algorithm for the articles, but every article that was studied by this reviewer was well worth the time spent.

One of these articles, written by the editor, gave an overview of his work on the `mirror system hypothesis' (MSH). This work has been widely discussed in the literature on evolutionary linguistics since the first edition of this book, and when confronting it for the first time may seem like a radical hypothesis. Such skepticism is aggravated by the lack of any historical record for the structure of the brain, and so any theories on language evolution will remain more tentative as compared to other scientific theories. The editor though wants the reader to consider evidence for the mirror system hypothesis that is drawn from existing life forms. Thus he proposes that we examine the "mirror system" for grasping in monkeys, which he asserts contains `mirror neurons" that are activated when the monkey performs a specific hand action and when it only observes a human or other monkey performing a similar action. The MSH is the assertion that the matching in the neural code between observation and execution occurs in the common ancestor of monkey and human. Further, this matching explains the notion of language `parity', which asserts that a spoken utterance has essentially identical semantics between speaker and listener. The editor reviews his ideas on what brain mechanisms are responsible for language and grasping, and whether a mirror system is indeed present in humans. Experiments using proton emission topography support his thesis to some extent, but he cautions that the a lot more work needs to be done before one can make definitive conclusions. His thesis though is a plausible one on the surface, and interesting in that it proposes that language originally evolved not from a need for communication but from a need to recognize a set of actions. "Language readiness" then, resulted from an extension of the mirror system from being able to recognize single actions to being able to imitate compound actions. A natural question to ask here is why sophisticated grammatical constructions, some of them semantically awkward and of no practical value, would evolve from the mere need to imitate, which itself is not really complex from any reasonable measure of complexity. The editor is aware of these kinds of objections, for in the article he addresses them under the guise of `protospeech', wherein he postulates two evolutionary stages for its development. His assertions in this regard are interesting for they involve the need for cooperation between two or more areas of the brain. Along these same lines, and even more fascinating, is the editor's discussion on neuronal models for the mirror system, for when he proposes a canonical structuring for sentences he is actually asserting a kind of "entanglement" (he does not use this terminology in the article) between the F5 area and its mirror.

Review of First Edition:
This complilation of articles by leading experts in the field gives an excellent overview of studies in cognitive theory and the theory and applications of neural networks. The first two parts of the book give an overview and background of the properties of neurons and gives guidance to the reader on what sequence the articles are to be read. This reviewer did not read all of the articles, but only those that piqued his interest. such as the following articles which are particularly well-written and informative: 1. "Applications of Neural Networks": Outlines the diverse applications of neural networks to signal processing, time series, imaging, etc. 2. "Astronomy": Neural network applications in astronomy, such as adaptive optics and telescope guidance. 3. "Chains of Coupled Oscillators": Their connection with the lamprey central pattern generator. 4. "Chaos in Axons": An excellent review of chaos experimentally in squid axons and numerically with nerve equations. 5. "Collective Behavior of Coupled Oscillators": A study of the phase and complex Ginzburg-Landau model. 6. "Computer Modeling Methods for Neurons": Good overview of numerical modeling of neurons. 7. "Computing with Attractors": Overview of omputing and feedback networks with attractors and a fascinating discussion of the possible existence of attractors in the brain. 8. "Constrained Optimization and the Elastic Net": Useful discussion of application of neural networks to optimization problems. 9. "Data Clustering and Learning": Good discussion of parameter estimation of mixture models by parametric statistics and vector quantization of a data set by combinatorial optimization. 10. "Diffusion Models of Neuron Activity": Discusses 1-dimensional stochastic diffusion models for the neuron membrane potential. 11. "Disease: Neural Network Models": Interesting overview of neural net computational models of various mental illnesses. 12. "Dynamics and Bifurcation of Neural Networks": Discussion of neural nets and their behavior as dynamical systems. 13. "Emotion and Computational Neuroscience": Fascinating discussion of computational models of emotion. 14. "Investment Management": A discussion of tactical asset allocation neural network methods in asset management. 15. "Learning and Centralization: Theoretical Bounds": Overview of computational learning theory. 16. "Locust Flight": Interesting neural network study of the locust flight system. 17. "Neural Optimization": Discussion of combinatorial optimization using Ising and Potts neural networks. 18. "PAC Learning and Neural Networks": Overview of the Valiant "probabilistically correct learning paradigm in neural networks. 19. "Protein Structure Prediction": Neural network applications to prediction of protein secondary structure. 20. "Schema Theory": Extremely interesting overview of schemas. 21. "Speech Recognition: Pattern Matching": Excellent discussion of the applications of hidden Markov models to speech recognition. 22. "Statistical Mechanics of Neural Networks": Discussion of the use of the Hopfield model in neural networks. 23. Vapnik-Chervonenkis Dimension of Neural Networks": Very interesting discussion of the VC-dimension of neural networks.

Look through this book to convince yourself that an exact brain theory does not exist. The arrangement of the articles by the first letter of their title tells it all (consider classifying animals by the first letter of their name). The editors wrongly assume that mathematical methods equal theory; actually, theory is a small conceptual tent under which a large number of experimentally established facts can be gathered. In most cases, mathematics is a very useful tool in pitching this tent, but it has little to do with the tent itself.

An exact theory of the brain may be possible and we are in dire need of it. Unfortunately, nobody has come up with it yet. This book is an encyclopedia of various mathematical methods that have been used to solve various neuroscience problems. These methods and solutions are as diverse as the problems themselves. Don't look for common themes in this book. If you are looking for a unified brain theory, you'll be much better off reading standard neuroscience textbooks. I do hope one day we'll be able to cast these vague ideas into something precise and, most likely, mathematical. Sadly, not today. I own a copy of this book and use it to remind me why and how we have failed so far.

It should be kept in mind that it is not at all clear that "neural" networks can emulate consciousness. They may or they may not. Firstly, a single neuron resembles a computer processor in its complexity and is a constantly evolving entity. Secondly, only 10% of brain cells are neurons and the remaining 90% (glial cells) now too appear to be involved in information processing. At a more fundamental level, consciousness may be less algorithmic and computational than we expect. Finally, the brain and the reality "outside the brain" are a two-way street. As the great neuroscientist Cajal put it, "As long as our brain remains an arcanum, the Universe, a reflection of its structure, will also be a mystery". If we assume the brain analyzes something, we need to define a reality independent of this analysis -- a hardly possible task if standard "input-output" approaches are used.

If the title of this book were "Current Mathematical Methods in Neurosciences", I'd have no problem giving it five stars.

November 2005: The chapters in the second edition are still arranged alphabetically. I refuse to believe neuro-mathematicians cannot think more coherently.

One final note for those looking for serious conceptual advances on the theoretical front: do no miss "Spikes: Exploring the Neural Code" (edited by F. Rieke) and "Decisions, Uncertainty, and the Brain: The Science of Neuroeconomics" by Paul Glimcher.

Research is tedious, but if you want to know the nitty-gritty of mind-brain theory and neural networking, this book is an invaluable resource for basic, relevant, and accessible papers on the subjects. Encompassing seminal works from an unusually broad range of disciplines, here is an outstanding reference for those concerned with the mechanisms of intelligence.

This is THE neural network and brain theory reference. Owning it is like owning an entire library, though much more compact.

If you take a look at the table of contents, you'll see the massive value in this book. If you're into neural nets and brain theory, or want to be, you need this book.

I'll start by admitting that I'm not a sci-fi thriller fan, but this book was recommended to me and I took a chance. I'm glad I did! This is an outstanding piece of work written by an individual who must know a great deal about high-technology advancements and the field of artificial intelligence. The book kept me enthralled and engaged every bit of the way. Anyone who likes thrillers, knows anything about computers and the advancements made, underway, and those yet to come, will find this book a must read. Mr. Rockwood has a promising future for writing and I look forward to reading more of his work.

When I read the opening of this novel, I had high hopes for it. Andy Rasmusson is a computer science professor at Cornell University and he has invented sentient non-organic beings. In other words, they are intelligent, self-aware computers. For lack of a better term, the computers are called Bee and Cee. The story opens with Bee being a guest on a television talk show hosted by a man named Ragu. There is a great deal of public animosity against the non-organic sentient entities and Ragu contributes to this hostility.
Shortly after the appearance, the administration and government agents try to get Andy to take a position on upcoming anti-sentient legislation. When he refuses, he is placed on unpaid administrative leave and asked to leave the university. The government then begins a program of persecution, intimidation and tries several times to arrange a fatal "accident." He is slowly being poisoned by the police bracelet and he is denied contact with his former colleagues who may be in a position to help him.
Andy eventually lands in the hospital due to the poisoning and the government plot is exposed. The poisoning has caused his liver and kidneys to fail, so the solution suggested by Cee is to have them regenerated using nanotechnological techniques. The conspiracy was so far ranging that it brings down the President of the United States and Andy is now a hero to the nation. A great deal of the prejudice against sentient non-organic beings now evaporates and the book closes with an episode of the Ragu show. This time Ragu is very respectful of the sentient non-organic beings and their future is assured.
The problem with this book is that once the opening is done, it becomes just another massive government conspiracy book. Government agents are ubiquitous in Andy's life; they plant bugs everywhere in his residence, have him under constant physical surveillance, block all his communications and cancel his credit cards. However, even though they have all this power, at the end the government agents prove inept and public pressure brings them down. It would have been so much better if the plot would have involved the decision-making process of the non-organic sentients. Something along the lines of Isaac Asimov's robot stories and the three laws of robotics. Fundamentally, the plot is not about the social and political consequences of a sentient computer and artificial intelligence. They are only background devices needed to launch a story about a government conspiracy.

So much of Science Fiction has been dominated by the techno-thriller prolepses of Gibson and the vast rambling scientific recreations of Stephenson and all their imitators that the philosophical and speculative roots of the genre seem all but lost at times. "How Noble in Reason" is a return to the brave, imaginative values of H. G. Wells and Jules Verne. Like those pioneers Rockwood begins with a daring and original speculation for a real future which he then explores through the lives of credible, conflicted characters about whom we come to care deeply.

The novel also feels almost Nietzschian at times, both in the way it rapidly and wryly touches numbers of philosophical issues and its central, highly original speculation. Nevertheless, like the stories of Wells and Verne, it is great fun to read. Rockwood is a scientist and Mathematician and he knows how human science actually is and how it's done. That experience lends the book the same level or authenticity that has made the books of Tom Clancy so successful.

Read the book because it is good, original Science Fiction. And don't be surprised if you find afterwards that you see the world you live in now in a very different way.

The genre of science fiction is not my forte', but I read this book because I've known Alyn from the time we were in grade school and wanted to be supportive of an old friend. I was impressed with Alyn's technical mastery of computers and of the idea of computers being designed to have feelings and character traits, an idea I had never considered. I was mostly impressed, however, with the symbolic nature of the book. I related to the theme of Job in the story, and ultimately of the restoration of things taken away, as Job also experienced. More than that, I was touched by the love a father has for a son, and tributes celebrating that love. Alyn contibutes to the lives of the masses through personal and individual accomplishment. I appreciated the insight I received as a result of reading this book.

It is the year 2051 and Dr. Andreas Rasmusson's comfortable existence is about to unravel. The underlying source of the destruction ... a three-year-old unsolved murder of his closest friend, Bee, a nonorganic sentient. Ostracized from the Cornell University academic community, Rasmusson finds temporary solace within the bucolic lifestyle of Colorado. Yet, peace is short-lived. In his quest to prove his innocence and solve the crime, Rasmusson is plunged into a world of deceit, espionage, and madness.

***

When I began reading How Noble in Reason, I anticipated it to be a murder mystery sci-fi thriller, and it was! The story takes the reader on an exciting emotional roller coaster ride with shocking plot twists and turns. Author Alyn Rockwood drops enough red herrings to confuse but not sidetrack to extreme.

So, what sets this novel apart from other techno-thrillers? How Noble in Reason is a powerful love story! The prevailing theme of unconditional love flows through the story on many levels: between human intelligence and artificial intelligence, father and son, boy and dog, husband and wife, lovers, friends, nature, and even enemies. In a futurist world, where artificial intelligence is a perceived threat to the human race, love is the one tie that binds humanity and machine.

Alyn Rockwood writes in a crisp Michael Crichton style, with the perfect blend of suspense, techno-speak, subtle humor, underlying romance, and human drama. It is one of the few books I have read with several "I never saw that coming" moments. How Noble in Reason is destined for the New York Times best-seller list!

This is an interesting introduction to artificial intelligence, but it is rather outdated. In addition, while it gives a general overview of the entire field (at least how the field stood during the writing of the book), it doesn't give as man concrete examples, or as many code examples, as an in-depth developer might want. I would recommend Russell & Norvig's Artificial Intelligence: A Modern Approach for the serious developer, and forego this guy.

I was thinking of purchasing an introductory book on AI for my 14 year old son since he was so interested in robots and automation. Apparently, this book is beyond him. I am not sure whether there is an AI book for children.

Having last been printed in the mid 80's some of the information is getting a little dated at this point, but for anyone new to the subject it is a very good read and an excellent introduction to the feild of AI.

I actually picked up this book at the discount bin at a local bookstore. I had always been interested in A.I research, and this deal was irresistable. However, I think this book is worth alot more, and provides more insight into the field than many of the current popular books on the subject.

This book basically goes into A.I research and leaves alot of the philosophical issues at a minimum. Basically you can look at this as a real text book about the subject of A.I. By my expirience, it isn't easy to find outside of the popular science market.

The topics that this book covers is extensive. The first few chapters go into subjects like Game Theory, and the problem-state models of A.I. He also gives a very extensive overview of the contruction of the human brain and its paralells to finite state machines. What I found particularly interesting was his coverage of many Turning Machines. Later, the author takes you into more rigorous examples dealing with problems of Theorem proving. And definitely one of the most interesting chapters was his coverage of natural languages.

I have owned this book for about 2 years, and although I do not read it faithfully everyday, I do find myself reading this book extensively for periods of 2-3 months. The material will demand a great deal of work on the behalf of the reader. As this book deals with many abstract concepts in mathematics that can be confusing to the untrained reader. Admitedly, i had to stop reading this book for a little while and take 4 months to get to a functional level of linear algebra, before I could fully comprehend the tranformation he showed chapter 6.

This is a must buy for anyone who wants to get their feet wet in the field of A.I. And with such a small price tag, you really cant lose.

I was searching for a book that will introduce me to artificial intelligence concepts; and although this book seemed old (1985), I bought it because of it's low price. Then when I opened it for the first time I was amazed how great it is. It worths a whole lot more. I soon found out that some concepts are for ever, and no matter how old they will be current in the future.

it is a very helpful book for those who want to get the outline of evolutionary computing. it will offer a solid foundation for further study.

The authors emphasise from the get-go that this book is meant as a practical introduction to the application of evolutionary computing. It is not a high brow, abstruse monograph. (Which indeed Springer texts often are.)

The level of discussion can be adequately understood by someone with a good background in computing and hopefully also in some science or engineering field. Certainly, there are important abstractions that must be mastered. Like how the evolutionary search can be seen as a path across a fitness landscape or potential energy surface. But there appears to be a careful explanation of the minimum necessary maths to convey an idea. And where a chapter's references might point to more specialised texts or journal papers that give a fuller math treatment.

It may well be, as another reviewer remarked, that there is insufficient detail in some passages of this book. But perhaps the text is not meant to be a low level "user's manual" type of discussion.

If you do find this book useful, consider a more advanced text, "Foundations of Genetic Programming" by Langdon and Poli, also published by Springer. It takes you deeper into the subject.

I taught our introduction to evolutionary computation class from this book. It is a well rounded introduction to the topic covering most of the introductorty material you would expect. There is an real dearth of good introductory books for EC. This is probably the best because of its breadth. Its weakness is its lack of detail. It would not hurt if they covered the same material in about 50% more pages. As soon as they start a topic its over and on to the next topic. But if you are new to the field they give plenty of references and touch on most topics in enough detail for students to implement. All in all a good solid job.

I have used evolutionary programming in my research in the past and have read several books on the topic. This is one of the most well written books available, that can easily be read by a beginner despite its depth. The conclusions that they draw are logical and supported by the appropriate references (I was not impressed with the theory and results in the field, but this has nothing to do with the quality of this book).

This is an excellent textbook which covers most aspects of the Evolutionary Computing. It's suitable for all levels. It's easy to follow, rich in content and has many references (439 to be precise) for further information. The table of contents from the book's web site is as follows:

1. Introduction
2. What is an Evolutionary Algorithm?
3. Genetic Algorithms
4. Evolution Strategies
5. Evolutionary Programming
6. Genetic Programming
7. Learning Classifier Systems
8. Parameter Control in Evolutionary Algorithms
9. Multi-Modal Problems and Spatial Distribution
10. Hybridisation with Other Techniques: Memetic Algorithms
11. Theory
12. Constraint Handling
13. Special Forms of Evolution
14. Working with Evolutionary Algorithms
15. Summary
16. Appendices
17. Index
18. References

Recommended to everyone interested in EC.

In this nearly twenty year old book, the author contends that advancing technology and the force of economic competition will lead inevitably (and in a span of mere decades) to a world in which machine intelligence vastly exceeds human intelligence. In chapters 3 through 6 the author gives a fascinating look at some of the possible features of that transhuman, post-biological world. Those chapters are as interesting and thought-provoking as any that have appeared in more contemporary treatments. Where the book does show it age, however, is in the first three chapters. There the author reviews the history of computer technology, and then succumbs to the shop-worn refrain of many classical AI researchers - "If only we had a computer that is 100 (or 1000 or 10000) times as powerful as today's machine, then we could program a human-equivalent intelligence". He even predicts on page 23 that "a general-purpose robot usable in the home" will be available within ten years. Well, today we have the computer power he was hoping for and still no general-purpose robot. Bottom line: if you want a fascinating look at what a world with superintelligent machines might be like, then buy this book and start reading at chapter 4. If you are interested in how we might actually achieve such a world then consider buying a copy of "On Intelligence" by Jeff Hawkins.

I picked up this book, expecting to learn a little bit about where we're headed with our computers, and the consequences therein. I learned all that--but I got even more than I bargained for. I have to say, the prologue in and of itself blew me away. I had never quite thought of humans as the first step in a bigger evolution. I read this book six months ago, and I haven't been able to get the implications of it out of my head since. If you're looking for the big answers--like "Why are we here?" and "What's the point?"--you may be like me and find more in here than in more traditional spiritual texts.

This book does a great job of exploring the future of robots, artificial intelligence, the human mind, and human identity. A few parts of it seem dated, but most of what the book describes seems likely to happen this century and to surprise the large fraction of the population which still hasn't given any thought to the possibilities this book describes.

This is a hard Hitting Strong AI book. It's the the land mark book the drew the line in the sand. If you wont to know what the strong AI position is this is the only book you have to read.

You wont feel special after reading this book... So much for being on the top of the evolutionary ladder

Moravec writes a good book but I think his ideas are a tad to far out there. He doesn't take into account the possiblility of people not wanting to have their minds transfered to machines. He appears to assume that it is inevitable. I personally agree with his goals but I suspect that the majority of the population would be strongly opposed.

Satisficing as in searching for "good enough" actions rather than the optimal ones is one of the many contributions Herbert Simon is most famous for, in addition to being one of the parents of Artificial Intelligence. Whether the topic is management decision making, economics, traveling, teaching, or computer programs, this Renaissance Man had a life that many or most would envy.

Herbert Simon is a true example to exemplify the benefits of multi-discipline efforts as one subject does not always know the answers. If anyone is interested in building their own latticework of mental models then the life of Mr. Simon is one to emulate. As this is not your average biography, expect to be challenged as the reading may take you to subjects that you are unaware of or have been exposed to. However, this is what makes the experience worth the trip as my many notes and earmarks attest to.

As his life was about scientific discovery to quote, "I have sketched the theory of scientific discovery to which my study of these problems has led me. It is not a theory of global rationality but one of human limited computation in the face of complexity". Yes, we live in an evermore complex world and I am glade I have some of Mr. Simon's mental models to guide me through it.

If you are a graduate student of management, this is must for you. Simon is an icon in the field of decision-making. Much of his work has inspired contiuned research in the field of decision-making. An extraordinary man with extraordinary vision.

The late Herbert Simon was a veritable renaissance man. His autobiography, "Models of My Life," discusses the single thread that underlined all of his intellectual conquests in artificial intelligence, sociology, cognitive science, psychology and economics. This one thread, animated by philosophical positivism and ripe scientific thirst, was his deep obsession with modeling and researching decision-theoretic behavior.

It's interesting to note that even though decision theory (how intelligent agents percieve and act upon choices amid various modalities) serves as the impetus for Simons work, he uses "Models" instead of "Model" in the book's title. This is no accident. For you see, beautifully fitting of his memoir, this book delves into how Simon's one passion was his "heuristic" in choosing which of many paths he could have taken througout his life. The upshot: Simon's own life emulated the heuristic search (in AI) that he helped invent! Consequently, this lead him all over the globe, from Wisconsin to UChicago to Berkeley to Carnegie Mellon to China.

This book is also about the times of Simon: the positivistic turn in social sciences, the scientific fermet of the 1950's, the cultural tumult of the 60's, the death of behaviorism and the rise of cognitivism -- all along, peppered with intrigue of the politics of academia. Although the writing can get quite dry at times, his book is highly recommended.

This intellectual autobiography is not just a chronology of the particulars of a great intellectual life. It is a wonderful opportunity to obtain a coherent overview of the views and contributions of one of the twentieth century's great thinkers. Simon - political scientist with his Ph.D. from University of Chicago, founder of the new and emerging area of artificial intelligence, cognitive psychologist, Cargegie-Mellon faculty member, Nobel laureate for economics (1978), and contributing philosopher of science - was no dilitante. This book, which is written is a very accessible style, reveals the integrity and evolution of his thinking, which can be extracted only with relative difficulty from his large and diverse literary corpus. It is also an inspiring book for any person with an active intellectual life in science or philosophy.

Thomas J. Hickey, www.philsci.com

Herbert Simon's research contributes to human knowledge in many different areas, including economics, artificial intelligence, cognitive psychology, and organizational behavior. In each of the mentioned areas, his contributions are ranked among the most important and influential that even a scientist who focuses solely in one area finds hard to achieve. The testimony is the top awards that the community in each discipline bestowed upon him--the Nobel prize is only one of which.

The secret of this interdisciplinary success is that he is, in his own word, a "monomaniac", studying only one thing--human decision process--for fifty years. The field of his own choosing is not bounded by usual academic disciplines, however, and he did study it from many different aspects, from the levels of individual cognition to organizational decisions, using tools as varied as mathematics, computer simulations, and human subjects.

This book detailed his own account of the various aspects of his life, personal and professional, in a sincere and direct prose. From the childhood that undoubtedly helped set the tone for his later accomplishments, the way he managed and nurtured new academic thoughts that later grown into full-fledged disciplines (artificial intelligence, cognitive science, and, less prominently, bounded rationality), to the philosophy of working and living including brief exposures to familial life, we can learn tremendously from hise xperience, decisions, and actions.

How could he achieve as much as he did? We can glean several lessons from his stories. He collaborated extensively. He learned a great deal from the outstanding individuals he respected. He had a love for truth and rigor in reasoning. An empiricist who firmly believed that any valid theory must be based on empirical facts, he did not hesitate to fight against widely held beliefs conflicting with facts. His work on bounded rationality which helped earn him the Nobel Prize is an outstanding case which his stubborn, and valid, arguments against mainstream theories brought a valuable alternative viewpoint to the world. Strong passion and the ability to break out of the mold and stand tall under storms are important characteristics exemplified by many past giants, including Galileo, Columbus, and Einstein.

Not just a normal autobiography, but the story of a distinguished life we all can learn from.

This is an OK book for a intro level tutorial. From reading some of the other reviews here I bought it thinking it would be what I needed. If you want indepth information on using Robo Help this book is not it. All functions are not covered just basic ones are.

I've been a Technical Writer for over a dozen years, and have spent over a decade writing on-line help for various systens, and I can honestly say that this is the one book that you need to buy if you are going to use RoboHelp as your Help Authoring Tool (HAT) for the World Wide Web.

RoboHelp (RH) has dominated the WinHelp Authoring field for many years, and is extending its expertise into the area of web-based help. Those who have used RH before need to learn some new concepts, and those writing help for the first time are well advised to find a native guide to help with the unfamiliar territory.

Fortunately, John Hedtke and Brenda Huettener are skilled and expert guides, providing the information that users need when they need it (and sometimes before they know they need it; the chapter on "Creating a Documentation Plan" is a must-read for anyone who wants to reduce the number of headaches they might encounter. It's not JoAnne Hackos' _Managing Your Documentation Projects_, but they do give you the information you need to get the work done without feeling stupid or overwhelmed.

This is a book that you keep close at hand to answer the "how do I do ____?" questions that always come up when creating a documentation set. The clear and easily followed explanations of concepts and techniques are well-illustrated with screenshots, and there is just enough theory for users to understand why things have to happen in a particular way.

As I said at the top, if you are going to use RoboHelp as your Help Authoring tool for the Web, this is the book to get. Even if you are not going to be using RH, the book is worth getting for the Document Development and Help Logic material it contains.

John Hedtke and Brenda Huettner are knowledgeable professionals in the online Help field, and RoboHelp for the Web really showcases their knowledge. I'd recommend this book to any online Help developer. Newbies will benefit from the simple explanations and step-by-step procedures in the book. More experienced technical writers will find themselves learning quite a bit from latter chapters.

RoboHelp for the Web is a fantasically helpful book if you want to build an online help system. Both the authors are pros, and the book is written in an informative and easy-to-comprehend style. The book has information valuable to beginners and veterans alike. I really liked the clear explanations for adding images and special effects, not to mention templates, skins, context-sensitive help, and how to work with Microsoft HTML Help Windows and WebHelp Enterprise Windows. I?ve been following the writing of John Hedtke for many years because of his clear prose and concise explanations. He and Brenda Huettner have written an invaluable guide. This is a definite MUST HAVE for anyone working with online help systems.

As a former instructor on how to create and manage help projects as well as a help developer with over a decade of experience in the trenches, I can unequivocally state that "RoboHelp for the Web" is an invaluable resource for anyone involved in help development: beginning developers, seasoned developers, developers returning to the fold after forays into other technologies, managers, and consultants.

Of course I expected complete how-to information, and the book did not let me down. But there's so much more.

Beginners will welcome explanations of the advantages, disadvantages, and most likely uses for the various types of help.

Seasoned veterans will appreciate the extensive sidebars and tips on how to handle technology issues associated with new server-based features.

"Returning" developers will find it easy to discover what's new and/or different.

Managers and consultants will embrace the "Advantages to Using Online Help" section - it's great source material for selling executives on the idea of moving from printed to online doc.

And the section on "Creating a Documentation Plan" is a must-read for anyone who needs to "sell" any documentation project to management or clients.

People aren't computers. Human beings live in a real world of scarcity and constraint. Even though time and information may be scarce, human beings must make high-stakes decisions. Probability and logic offer models for the thought process of choosing between alternatives, but decision makers often do not have enough hours, data and skill to use these sophisticated approaches. Fortunately, some rough and ready cognitive shortcuts perform as well as or better than the most elaborately sophisticated models - at least in the real world context of limited information and time. Working with the ABC Research Group, authors Gerd Gigerenzer and Peter M. Todd explore some of those shortcuts, called "heuristics." They discuss in length and depth a series of experiments that demonstrate the value of heuristics. This is not light reading. It requires a level of comfort with academic style, mathematics and symbolic logic. Readers unfamiliar with cognition literature may find it a struggle - but we believes that those who persevere will find enough new insight to make the effort worthwhile.

Gerd Gigerenzer is probably THE guru in heuristics - the art of picking a few shorthand rules to help us make complex decisions - but I found other works of his (Adaptive Thinking, Bounded Rationality) pretty dry going. By contrast this volume - a collection of stimulating, sometimes provocative essays by members of the ABC Research group (the centrer for Adaptive Behavior and Cognition) explores many facets of Heuristics and even puts heuristics to the test against other more computationally complex techniques to pick the outcomes for several complicated problems. Time and again, the simple rules of thumb out-perform the grindingly thorough statistical routines. For anyone researching human behaviour, the implicit challenge is to stop asking huge batteries of questions - and to look instead for the little telltale rules by which people navigate their complicated environments.

I'd say that if you were just starting to look at heuristics, then this this volume of essays would be a good starting point. Even if you skip the super-technical pieces, there's plenty of thought provoking material written in a lively, unexpectedly "human" style.

It's really meant for a technical audience since this stuff is so cutting edge, but you shouldn't wait till the results appear in Time magazine. The experiments and writing are very easy to understand, very clear. And you will be amazed by the simple ways in which our brain takes shortcuts in reasoning -- both making it stupid and making it smart. Be careful next time you try to reason using probabilities, you're better off using frequency.

My own background is in philosophy, where this type of work has been very important in undermining the assumption that humans are rational. We aren't. You should probably read Kahnemann and Tversky's books before coming to this though, since this work adds an interesting spin to the old irrationality debate: maybe some of it is GOOD for us!

Whether you like a book depends on what information you're looking for. i make computer models of human behavior so this book, which is easy to read but filled with concrete solutions and lots of supporting dat, was near-perfect for me

As a note, i'm picky when it comes both to writing and thinking. And i hate most books written by academics. Even the ones with good information (eg, Fodor's Modularity) are hard to read and filled with confusing, field-specific words. Not this book. It's really well written. Written in plain English, very few assumptions, very thorough analysis, lots of self-criticism, lots and lots of data (OK, that part is boring and can be skipped, but it's comforting to know it's there)

What's it about? Common AI, psych and economic decision and learning algorithms (decision trees, neural nets, Bayes, multiple linear regression, etc.) are compared to several absurdly simple algorithms the authors believe real humans use. The various approaches are compared and evaluated on the basis of performance, accuracy on training data, accuracy on test data (generalization) and amount of input data required. Tests are on the standard UC Irvine data learning test sets. Comparisions, outcome explanations and relevance to the human mind and the real world are provided. Explanations and analysises are easy to understand and pretty convincing

i've decided to use a lot of what was in this book in my software, things that have made my agents more natural and easier to implement. i absolutely love this book

As someone interested in the practice and theory of decision making, I came upon this book via a number of "listmania" lists that reccomend it. The first few chapters got me excited about the subject matter. The authors promised to present a new model for decision making, one that was simple, and one that works.

The ensuing pages compare several theoretical models, such as Multiple Linear Regression and Dawes Rule to their own Take the First and Take the Best models.

Most of the tests were simulated on a computer. You would feed each decision making model into the computer, and then feed in various data for it to make decisions on. One popular test is "Which is the most populated German City." The computer had data on various German Cities with populations over 100,000. It also had several indicators, such as whether it has a soccer team, or a rail system, or is a state capital. The system would present two cities, with the indicators, and the decision making model would figure out which was the most populous one.

Right now I'm in a chapter called "Bayesian Benchmarks for Fast and Frugal Heuristics." It's about halfway through the book, and I'm not sure I'll finish. While the second half sounds interesting, this book is highly academic and the authors are concerned with presenting proofs for everything they say, in detail. Sort of like a victorian novel that starts of by telling you what it's going to tell you, and then tells you several times. I may skim it because I do find the subject matter intereting.

I certainly don't regret buying this book, having mathematical models for decision making is certainly handy (as someone interested in AI), but I wouldn't call it light reading, nor would I reccomend it to a manager interested in the decision making process.

I found much more interesting "Sources of Power" by Gary Klein. Indeed, I consider Sources of Power to be one of the most informative and most entertaining books I've ever read, and wish more like it existed.

In summation, I found this book to be highly academic and theoretical. If you are a human being interested in the decision making process as it is carried out by humans, I reccomend the more hands-on Sources of Power by Gary Klein. If you are interested in simple, statistical models for decision making (the kind you can teach a computer), then pick up this book.