Learn Chess the Easy Way with These PDF Books
In this book, the highly experienced author and coach Neil McDonald analyses the finest examples of pressure play. In doing so he teases out the fundamental concepts that enable players like Carlsen to torture their opponents mercilessly.
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Neil McDonald became a grandmaster in 1996 and a FIDE trainer in 2017. He is a regular coach of the England Junior team at international events. Neil has written numerous books on openings, endgames, tactics and strategy as well as biographies of famous players. He lives in Gravesend in Kent, England.
The chess ending (KRKa2) has been studied using decision trees, neural networks and human reasoning to build a classifier for this ending, and for the discovery of convenient chess attributes. These chess attributes will serve for testing new ideas in planning. The idea is to investigate whether good automatically learnt policies for a planning problem can be generated using training examples along with evolutionary algorithms. The training examples, used as input to the learning algorithm, describe specific descriptions of a number of solved instances in one domain; then to improve the learnt policies obtained from the training examples, the policies should evolve. We believe that the domain of games is well-suited for testing these new ideas in planning.
Recursive depth-first searching dominated computer chess and other fields of computer game-playing since their nascent days in the early 1950s. While surveys and introductory texts on the subject area abound, we specifically like to mention and recommend only two of them. The excellent overviews by Kaindl  and Marsland  concentrate on the computer-chess related aspects of the most important search techniques and their successful application in real programs. We briefly introduce the game of Chess itself before diving into our own explanations of basic and advanced search methods and their implementation.
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