How to teach AI to play Games: Deep Reinforcement Learning.

Two machine-learning procedures have been investigated in some detail using the game of checkers. Enough work has been done to verify the fact that a computer can be programmed so that it will learn to play a better game of checkers than can be played by the person who wrote the program.

Machine learning using the game of checkers

The studies reported here have been concerned with 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. While this is not the place to dwell on the importance of machine-learning procedures, or to discourse on the philosophical aspects,1 there is obviously a very large amount of work, now.

The Implementation of Machine Learning in the Game of Checkers.

Samuel’s Checkers Player is the first machine learning system that received public recognition. It pioneered many important ideas in game playing and machine learning. The two main papers describing his research (Samuel 1959, 1967) became landmark papers in Artificial Intelligence. In one game, the resulting program was able to beat one of.A new signature-table technique is described together with an improved book-learning procedure which is thought to be much superior to the linear polynomial method. Full use is made of the so-called “alpha-beta” pruning and several forms of forward pruning to restrict the spread of the move tree and to permit the program to look ahead to a much greater depth than it otherwise could do.An important precursor to Tesauro's TD-Gammon was the seminal work of Arthur Samuel (1959, 1967) in constructing programs for learning to play checkers. Samuel was one of the first to make effective use of heuristic search methods and of what we would now call temporal-difference learning.


Checkers is a classic board game, dating back to around 3000 BC. It is very simple, but a lot of fun! Checkers is known as Draughts in England and there are multiple variations of it all around the world. The game is played on an 8x8 chequered board, essentially a chess board. Each player starts with 12 pieces, placed on the dark squares of the.Samuel’s Checkers Player is the first machine learning system that received public recognition. It pioneered many important ideas in game playing and machine learning. The two main papers describing his research (Samuel, 1959, 1967) became landmark papers in Artificial Intelligence. In one game, the resulting program was able to beat one of.

Machine learning using the game of checkers

SOME STUDIES IN MACHINE LEARNING USING THE GAME OF CHECKERS (20 pages) Previewing pages 1, 2, 19, 20 of actual document. View the full content.

Machine learning using the game of checkers

Some studies in machine learning using the game of checkers (1959) by A L Venue: IBM Journal: Add To MetaCart. Tools. Sorted by: Results 1 - 7 of 7. Learning to predict by the methods of temporal differences by Richard S. Sutton - MACHINE LEARNING, 1988.

Machine learning using the game of checkers

Some studies in machine learning using the game of checkers. A. L. Samuel. posted on 01 April 2000. pdf (668 views, 206 download, 0 comments) Two machine-learning procedures have been investigated in some detail using the game of checkers. Submitted by. 0%? editor.

Machine Learning Comes To Kingsrow - The Checker Maven.

Machine learning using the game of checkers

Buy Some studies in machine learning using the game of checkers II: recent progress (Annual Review in Automatic Programming: Vol 6, part I) 1st ed by A.L. SAMUEL (ISBN: ) from Amazon's Book Store. Everyday low prices and free delivery on eligible orders.

Machine learning using the game of checkers

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 was the game of checkers.

Machine learning using the game of checkers

Creating this function requires some knowledge of checkers strategy, and is very time consuming. The latest Kingsrow has done away with these manually constructed and tuned evaluation features. Instead it is built using machine learning (ML) techniques which require no game specific knowledge other than the basic rules of the game.

Machine learning using the game of checkers

Machine Learning programs can be beaten once, but against an oppo-nent that does not change, it eventually will be able to beat it. The project that I am writing will learn how to play the game of checkers as it plays, by modifying itself after ever game played.

Machine learning using the game of checkers

Bibliographic details on Some Studies in Machine Learning Using the Game of Checkers.

LM101-002: How to Build a Machine that Learns to Play Checkers.

Machine learning using the game of checkers

Two machine learning procedures were described in some detail: (1) a rote learning procedure in which a record was kept of the board t Some Studies in Machine Learning Using the Game of Checkam, IBM Journal 3, 211-299 (1959).

Machine learning using the game of checkers

Cite this chapter as: Samuel A.L. (1988) Some Studies in Machine Learning Using the Game of Checkers. II—Recent Progress. In: Levy D.N.L. (eds) Computer Games I. Springer, New York, NY.

Machine learning using the game of checkers

Abstract: Two machine-learning procedures have been investigated in some detail using the game of checkers. Enough work has been done to verify the fact that a computer can be programmed so that it will learn to play a better game of checkers than can be played by the person who wrote the program.