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Fermat's Library Some Studies In Machine Learning Using the Game of Checkers annotated/explained version.

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This is his seminal paper originally published in 1959 where Samuel sets out to build a program that can learn to play the game of checkers. Checkers is an extremely complex game - as a matter of fact the game has roughly 500 billion billion possible positions - that using a brute force only approach to solve it is not satisfactory. Samuel's program was based on Claude Shannon's minimax strategy to find the best move from a given current position. In this paper he describes how a machine could look ahead "by evaluating the resulting board positions much as a human player might do".


In Memoriam: Arthur Samuel: Pioneer in Machine Learning

AI Magazine

From 1949 through the late required to have his research more didn't finish 1960s, he did the best work in making vigorously followed up on. He was the computers learn from their experience. Programs for playing games often and what would be required to In 1949, Samuel joined IBM's fill the role in artificial intelligence reach human-level intelligence. Poughkeepsie Laboratory, where he research that the fruit fly Drosophila Samuel's papers on machine learning worked on IBM's first stored program plays in genetics. Drosophilae are are still worth studying.


In Memoriam

AI Magazine

Arthur Samuel (1901-1990) was a pioneer of artificial intelligence research. From 1949 through the late 1960s, he did the best work in making computers learn from their experience. His vehicle for this work was the game of checkers. Programs for playing games often fill the role in artificial intelligence research that the fruit fly Drosophila plays in genetics. Drosophilae are convenient for genetics because they breed fast and are cheap to keep, and games are convenient for artificial intelligence because it is easy to compare a computer's performance on games with that of a person.


On Thinking Machines, Machine Learning, And How AI Took Over Statistics

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Sixty-five years ago, Arthur Samuel went on TV to show the world how the IBM 701 plays checkers. He was interviewed on a live morning news program, sitting remotely at the 701, with Will Rogers Jr. at the TV studio, together with a checkers expert who played with the computer for about an hour. Three years later, in 1959, Samuel published "Some Studies in Machine Learning Using the Game of Checkers," in the IBM Journal of Research and Development, coining the term "machine learning." He defined it as the "programming of a digital computer to behave in a way which, if done by human beings or animals, would be described as involving the process of learning." On February 24, 1956, Arthur Samuel's Checkers program, which was developed for play on the IBM 701, ... [ ] was demonstrated to the public on television A few months after Samuel's TV appearance, ten computer scientists convened in Dartmouth, NH, for the first-ever workshop on artificial intelligence, defined a year earlier by John McCarthy in the proposal for the workshop as "making a machine behave in ways that would be called intelligent if a human were so behaving."


On Thinking Machines, Machine Learning, And How AI Took Over Statistics

#artificialintelligence

Sixty-five years ago, Arthur Samuel went on TV to show the world how the IBM 701 plays checkers. He was interviewed on a live morning news program, sitting remotely at the 701, with Will Rogers Jr. at the TV studio, together with a checkers expert who played with the computer for about an hour. Three years later, in 1959, Samuel published "Some Studies in Machine Learning Using the Game of Checkers," in the IBM Journal of Research and Development, coining the term "machine learning." He defined it as the "programming of a digital computer to behave in a way which, if done by human beings or animals, would be described as involving the process of learning." A few months after Samuel's TV appearance, ten computer scientists convened in Dartmouth, NH, for the first-ever workshop on artificial intelligence, defined a year earlier by John McCarthy in the proposal for the workshop as "making a machine behave in ways that would be called intelligent if a human were so behaving."