Arthur Samuel was an American pioneer in the field of computer gaming and artificial intelligence. He coined the term "machine learning" in 1959. The Samuel Checkers-playing Program appears to be the world's first self-learning program, and as such a very early demonstration of the fundamental concept of artificial intelligence (AI).
Samuel graduated from College of Emporia in Kansas in 1923. He received a master's degree in Electrical Engineering from MIT, and taught for two years as instructor. Samuel went to IBM where he would conceive and carry out his most successful work. At IBM he made the first checkers program on IBM's first commercial computer, the IBM 701. The program was a sensational demonstration of the advances in both hardware and skilled programming.
Since he had only a very limited amount of available computer memory, Samuel implemented what is now called alpha-beta pruning. Instead of searching each path until it came to the game’s conclusion, Samuel developed a scoring function based on the position of the board at any given time. This function tried to measure the chance of winning for each side at the given position. It took into account such things as the number of pieces on each side, the number of kings, and the proximity of pieces to being “kinged”. The program chose its move based on a minimax strategy, meaning it made the move that optimized the value of this function, assuming that the opponent was trying to optimize the value of the same function from its point of view.
Samuel's later programs played thousands of games against itself as another way of learning. With all of this work, Samuel’s program reached a respectable amateur status, and was the first to play any board game at this high a level. He continued to work on checkers until the mid-1970s, at which point his program achieved sufficient skill to challenge a respectable amateur.