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12 Kalah on Atlas A. G. Bell I INTRODUCTION This is a report on work done with the

AI Classics

The original intention was to demonstrate the on-line typewriter to visitors via a simple system which reacted to the user, in this case by refusing to be beaten twice in the same way at the game of Kalah. The mechanism to achieve this is a memory, built up from information obtained in previous games, which is stored on magnetic tape. The program was designed to keep the size of this memory to small proportions by implementing two mechanisms the author believes to be commonly used by humans when solving problems. The two mechanisms are: 1. ignoring irrelevant information in the sense that, although it exists, it is highly probable that its precise structure or properties cannot alter the relevant information or characteristics of the problem being considered, and 2. accepting positions close to a solution or win, providing the opponent is further from a win. Some of the difficulties of testing these ideas in practice are discussed and suggestions are made on how to overcome them, in particular with the game of solo whist.


Predicting The Performance of Minimax and Product in Game-Tree

arXiv.org Artificial Intelligence

The discovery that the minimax decision rule performs poorly in some games has sparked interest in possible alternatives to minimax. Until recently, the only games in which minimax was known to perform poorly were games which were mainly of theoretical interest. However, this paper reports results showing poor performance of minimax in a more common game called kalah. For the kalah games tested, a non-minimax decision rule called the product rule performs significantly better than minimax. This paper also discusses a possible way to predict whether or not minimax will perform well in a game when compared to product. A parameter called the rate of heuristic flaw (rhf) has been found to correlate positively with the. performance of product against minimax. Both analytical and experimental results are given that appear to support the predictive power of rhf.