The non-extensive entropic index q was adjusted adaptively from large to small with the decreasing neighbor to balance the neurons' distant and close neighborhood cooperation ability. A q-Gaussian function was taken as a neighborhood function in an SOM neural network, and the non-extensive entropic index q was larger to efficiently increase the output space of the q-Gaussian function. In order to increase the output space of neighborhood functions and enhance the neighborhood cooperation between neurons, a q-Gaussian self-organizing mapping (SOM) neural network was proposed for evaluation of the effectiveness of radar electronic counter-countermeasures (ECCM). Despite the null results, I explore how related hypotheses and studies can build on the comprehensive mancala database. Using historical and contemporary data, I do not find evidence for either hypothesis. I compile the first comprehensive database of mancala games in Africa matched to ancestral characteristics data, and for 18 African countries, to the Afrobarometer survey data. I revisit this hypothesis with better data and motivated by anecdotal evidence, introduce a contemporary hypothesis, origins of entrepreneurship hypothesis-that descendants of societies that played complex man-cala games are more likely to be engaged in non-farm self-employment today.
Anthropology literature suggests that these games may be associated with socioeconomic complexity of the ethnic groups-the so-called games in culture hypothesis. This study examines the correlational relationship between the historical playing of indigenous strategic board games (also called mancala) and the socioeconomic complexity of African ethnic groups as well as the incidence of entrepreneurial pursuits. Contrariwise, if it starts to play second, using the heuristic algorithm, it nearly always loses. Namely, if the computer plays first, the human opponent cannot beat it. Moreover, multiple-case experiments proved that the opening move has a decisive impact on winning or losing. It can be deduced that the proposed heuristic algorithm has comparable success to the human player and to low-depth tree-search solutions. Then, a round-robin tournament of all the algorithms is presented. Two sets of benchmark tests are made namely, a tournament where a mid–experienced amateur human player competes with the three algorithms is introduced first.
#MANCALA STRATEGY GOING SECOND VERIFICATION#
A simple C++ application with Qt framework is developed to perform the algorithm verification and comparative experiments.
Standard and modified mini–max tree-search algorithms are introduced as well. This review concludes that even if strong in-depth tree-search solutions for some types of the game were already published, it is still reasonable to develop less time-consumptive and computationally-demanding playing algorithms and their strategies Therefore, the paper also presents an original heuristic algorithm based on particular deterministic strategies arising from the analysis of the game rules. This paper primarily focuses on a review of Kalah history and on a survey of research made so far for solving and analyzing the Kalah game (and some other related Mancala games). From this viewpoint, the art of playing Kalah can contribute to cultural heritage. The Kalah game represents the most popular version of probably the oldest board game ever-the Mancala game.
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