Blondie24: Playing at the Edge of AI (The Morgan Kaufmann Series in Artificial Intelligence) review Ñ 0

review Blondie24: Playing at the Edge of AI (The Morgan Kaufmann Series in Artificial Intelligence)

Blondie24: Playing at the Edge of AI (The Morgan Kaufmann Series in Artificial Intelligence) review Ñ 0 Þ Blondie24 tells the story of a computer that taught itself to play checkers far better than its creators ever could by using a program that emulated the basic principles of Human grand masters or to databases of moves for the endgame moves or to other human expertise about the game of chekers With only the most rudimentary information programmed into its brain Blondie24 the program's Internet username created its own means of evaluating the complex changing patterns of pieces that make up a checkers game by evolving artificial neural networks mathematical models that loosely describe how a brain works It's fitting that Blond. Blondie24 is informative humorous and gripping Fogel begins by covering the history of artificial intelligence both as it currently stands and as Hollywood represents it showing where Hollywood's vision is slightly inaccurate or too far out of reach He holds HAL IBM 1 from the movie 2001 A Space Odyssey as the ideal artificial intelligence because it is a learning machine that can think and feel for itself but he says HAL is currently impossible What we can do is create a learning machine Fogel goes on to describe a project he and his partner Chellapilla worked on a learning checker's program that would eventually become Blondie24 They came up with the Samual Newell challenge for their checker's program could the program invents it's own checker features and rely on feedbacks only after a series of games have been played In opposition to most others chess and checkers playing games before Blondie24 does not start with pre programmed rules nor does it solve it's problems by brute force like DeepBlue by calculating every possible boards as far as it can go Instead Fogel and Chellapilla used a neural net with very fews features associated with checkers and created random generations that would then compete against each other and evolve to a new better generation After a certain number of generations the computer would have developed it's own checker features without human inputs and 'learn' how to play checkersI really liked this book not only for the clarity of the topic's presentation but also it had some technical details and references to technical papers This is important to me because I would like to try to recreate the neural net for tic tac toe which Fogel did for his master's and learn by doing

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Blondie24 tells the story of a computer that taught itself to play checkers far better than its creators ever could by using a program that emulated the basic principles of Darwinian evolution random variation and natural selection to discover on its own how to excel at the game Unlike Deep Blue the celebrated chess machine that beat Garry Kasparov the former world champion chess player this evolutionary program didn't have access to strategies employed by. I would like to rate this book between 3 and 4 stars It didn't blow me away but the underlying ideas are very interesting and well presented The book is presented as a story no spoilersThe main point he makes about AI in computer learning is important and profound We have computers like Deep Blue to play chess but these computers haven't actually learned anything They are hand fed the human knowledge Deep Blue can play chess but out of the box would fall flat on it's face in a game of Connect Four Fogel well illustrates this failure in the advancement of computer learning as well as why it's so challengingThis book sits between technical and accessible and balances pretty well Everything is presented in a narrative with some fun suspense and gradual introduction of ideas He introduces some algorithms at a high level with optional footnotes for further reading I didn't usually find the footnotes useful As I have a technical background I would have liked in depth explanations of some things leaning towards implementation details The concept of machine learning is rooted in a technical background I don't think a lay person would pick up this book with no prior computing experience Fogel could have taken liberty with the algorithm descriptionsAnother minor critiue is that some of the stories as part of the narrative are not exciting and perhaps could have been cut out Most of them are very nice Some things like the typed out explanation that LOL stands for laughing out loud adds some dating to the book and might warrant another printI would suggest this book to someone with an interest in machine learning Fogel is a good clear writer and there are many interesting and important ideas here

David B. Fogel º 0 summary

Blondie24 Playing at the Edge of AI The Morgan Kaufmann Series in Artificial IntelligenceIe24 should appear in 2001 the year when we remember Arthur C Clarke's prediction that one day we would succeed in creating a thinking machine In this compelling narrative David Fogel author and co creator of Blondie24 describes in convincing detail how evolutionary computation may help to bring us closer to Clarke's vision of HAL Along the way he gives readers an inside look into the fascinating history of AI and poses provocative uestions about its futur. What is thinking What is learningThe story of a project with the aim of developing a learning artificial intellegence Blondie24 is a program with a neural net and an evolutionary algorithm which without much guidance learned to play checkers and crack a rating of 2000It never reached the high performance of programs that have been explicitly programmed with rules but the way it reached its high function was extraordinaryA set of weights were assigned to programs on a random basis and the worst performing were culled; the remnants were used with slight random variation to parent the next generation and so onIt is interesting evidence for biological evolution and against the complexity argument of intelligent design as the program was set up with the most elementary model of what checkers was But I digressThe programs were not told how good any move would be or that they won or lost any game but were selected on how they performed on a set of five games Even so natural selection produced a superior model of play Rather than giving the programs rules the rules were generated by inheritance from their slected ancestral lines over many iterationsBLONDIE The program was entered on a checkers game site originally with a Obi Wan Jedi name but they found that males tended to get very nasty if they lost so they switched their identity to a female They got some undesirable responses there too but they got asked out on a lot of dates To play they would manually run the program to whatever depth it could go in the time limit and enter that move against the human