%0 Journal Article
	%A Ibidapo O. Akinyemi and  Ezekiel F. Adebiyi and  Harrison O. D. Longe
	%D 2009
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 32, 2009
	%T Critical Analysis of Decision Making Experience with a Machine Learning Approach in Playing Ayo Game
	%U https://publications.waset.org/pdf/3871
	%V 32
	%X The major goal in defining and examining game
scenarios is to find good strategies as solutions to the game. A
plausible solution is a recommendation to the players on how to play
the game, which is represented as strategies guided by the various
choices available to the players. These choices invariably compel the
players (decision makers) to execute an action following some
conscious tactics. In this paper, we proposed a refinement-based
heuristic as a machine learning technique for human-like decision
making in playing Ayo game. The result showed that our machine
learning technique is more adaptable and more responsive in making
decision than human intelligence. The technique has the advantage
that a search is astutely conducted in a shallow horizon game tree.
Our simulation was tested against Awale shareware and an appealing
result was obtained.
	%P 1893 - 1898