Try Dam: Digital Checkers Game Application Based on Machine Learning

Abstract

A traditional game like checker or dam is often played by people in the past during their free time. Despite their leisurely and compelling activities, the games stimulate the cognitive, social and emotional well-being of players, to plan the right strategy to win the game. However, moving along with the difference in time, traditional games that used to be often played by all sections of society are increasingly being marginalized by the younger generation. Due to the development of technology, the younger generation appears to be more inclined to play mobile games than traditional ones. The proposed solution to this problem is to create a traditional game in digital form; and this paper aims to develop a digital checkers game application using machine learning and to test the functionality and effectiveness of the game. The development of this digital checkers game applies agile model, combined with game design strategy. The Alpha-Beta Pruning algorithm will be used to produce a computer capable of playing checkers. Based on the game competition result, the player's winning rate decreases along with the chosen difficulty level. Once the difficulty level increase, players need to demonstrate their mastery to play against computer. The computer has gained increased information to defeat the opponent using various strategies using "alpha-beta pruning" technique. This digital checkers game is expected to increase awareness and passion among generation young towards the local traditional games. Expected game play experience from the application include entertainment and easy access especially using smart telephone device.

Assessment of Marine Tourism Carrying Capacity: A Case Study at Kapas Island Marine Park, Malaysia

“…Data collecting took place during May and June 2022, primarily on weekends and public holidays when it was predicted that more people would visit. A questionnaire was only given to one volunteer participant (who was 18 years old and above) from each group of visitors to minimize redundancy (Abdullah et al, 2023).…”