Norhan Hesham, Osama Abu-Elnasr*, Samir Elmougy
CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 175-190, 2021, DOI:10.32604/cmc.2021.015168
Abstract Many previous research studies have demonstrated game strategies enabling virtual players to play and take actions mimicking humans. The Case-Based Reasoning (CBR) strategy tries to simulate human thinking regarding solving problems based on constructed knowledge. This paper suggests a new Action-Based Reasoning (ABR) strategy for a chess engine. This strategy mimics human experts’ approaches when playing chess, with the help of the CBR phases. This proposed engine consists of the following processes. Firstly, an action library compiled by parsing many grandmasters’ cases with their actions from different games is built. Secondly, this library reduces the search space by using two… More >
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