Learning Strategies for Explanation Patterns:
Basic Game Patterns with Application to Chess

Yaakov Kemer

Department of Mathematics and Computer Science
Bar-Ilan University
52900 Ramat-Gan Israel
kerner@bimacs.cs.biu.ac.il



Abstract. In this paper we describe game-independent strategies, capable of
learning explanation patterns (XPs) for evaluation of any basic game pattern. A
basic game pattern is defined as a minimal configuration of a small number of
pieces and squares which describes only one salient game feature. Each basic
pattern can be evaluated by a suitable XP. We have developed five game-independent 
strategies (replacement, specialization, generalization, deletion,
and insertion) capable of learning XPs or parts of them. Learned XPs can direct
players attention to important analysis that might have been overlooked
otherwise. These XPs can improve their understanding, evaluating and
planning abilities. At present, the application is only in the domain of chess.
The proposed strategies have been further developed into 21 specific chess
strategies, which are incorporated in an intelligent educational chess system
that is under development.
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