Arnan Dwika Diasmara, A. W. Mahastama, Antonius Rachmat Chrismanto
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In the basic test, the results of the CBR test were obtained with the highest formulated accuracy of the 3 examiners, namely 97.101%. In testing the AI scenario as a referee, it is analyzed through colliding pieces and gives the right decision in determining victoryKeywords: The Battle of Honor, CBR, RBS, unity, AIAbstrak. The Battle of Honor merupakan permainan papan dimana 2 pemain saling berhadapan untuk menjatuhkan bendera lawannya. Permainan ini membutuhkan pihak ketiga yang berperan sebagai wasit karena pemain yang saling berhadapan tidak dapat saling melihat bidak lawannya. Solusi dari hal tersebut yaitu mengimplementasikan Rule-Based Systems (RBS) pada sistem yang dikembangkan dengan Unity untuk mendukung peran wasit dalam memberikan keputusan berdasarkan aturan permainan. Peneliti juga mengembangkan Artificial Intelligence (AI) sebagai lawan dengan menerapkan Case-Based reasoning (CBR). 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引用次数: 3
摘要
摘要基于决策和机器学习的《荣誉之战》棋盘游戏智能系统。《荣誉之战》是一款棋盘游戏,两名玩家面对对方,拿下对方的旗帜。这个游戏需要第三方作为裁判,因为玩家在游戏过程中看不到对方的棋子。解决这个问题的方法是在使用Unity开发的系统上执行基于规则的系统(Rule-Based Systems, RBS),以支持裁判根据游戏规则做出决定。研究人员还开发了人工智能(AI),而不是应用基于案例的推理(CBR)。CBR的应用得到了最近邻算法的支持,可以找到高度相似的案例。在基础测试中,CBR测试的结果是3位考官中配方准确率最高的,为97.101%。在作为裁判的AI场景测试中,通过对撞棋子进行分析,给出正确的决定胜负的判罚。关键词:《荣誉之战》,CBR, RBS, unity, AI。《荣誉之战》(The Battle of Honor)《荣誉之战》(The Battle of Honor)二叠纪人都是这样的,他们都是这样的,他们都是这样的,他们都是这样的。Solusi dari hal tersebut yitu mengimplementaskan Rule-Based Systems (RBS) pada system () yang dikembangkan dengan团结untuk mendukung peran是dalam成员keputusan berdasarkan aturan permainan。人工智能(AI)基于案例的推理(CBR)。penerapcbr didukung dengan算法最近邻untuk menencari kasus yang memoriliki tingkat kemiripan yang tinggi。帕达企鹅dasar didapatkan hasil uji CBR登安精度杨迪鲁姆斯坎tertinggi dari 3企鹅yaitu 97,101%。企鹅在这里的情景是:企鹅在这里的情景是:企鹅在这里的情景是:企鹅在这里的情景是:企鹅在这里的情景是:企鹅在这里的情景是:Kata Kunci:荣誉之战,CBR, RBS,团结,AI
Sistem Cerdas Permainan Papan The Battle Of Honor dengan Decision Making dan Machine Learning
Abstract. Intelligent System of the Battle of Honor Board Game with Decision Making and Machine Learning. The Battle of Honor is a board game where 2 players face each other to bring down their opponent's flag. This game requires a third party to act as the referee because the players cannot see each other's pawns during the game. The solution to this is to implement Rule-Based Systems (RBS) on a system developed with Unity to support the referee's role in making decisions based on the rules of the game. Researchers also develop Artificial Intelligence (AI) as opposed to applying Case-Based reasoning (CBR). The application of CBR is supported by the nearest neighbor algorithm to find cases that have a high degree of similarity. In the basic test, the results of the CBR test were obtained with the highest formulated accuracy of the 3 examiners, namely 97.101%. In testing the AI scenario as a referee, it is analyzed through colliding pieces and gives the right decision in determining victoryKeywords: The Battle of Honor, CBR, RBS, unity, AIAbstrak. The Battle of Honor merupakan permainan papan dimana 2 pemain saling berhadapan untuk menjatuhkan bendera lawannya. Permainan ini membutuhkan pihak ketiga yang berperan sebagai wasit karena pemain yang saling berhadapan tidak dapat saling melihat bidak lawannya. Solusi dari hal tersebut yaitu mengimplementasikan Rule-Based Systems (RBS) pada sistem yang dikembangkan dengan Unity untuk mendukung peran wasit dalam memberikan keputusan berdasarkan aturan permainan. Peneliti juga mengembangkan Artificial Intelligence (AI) sebagai lawan dengan menerapkan Case-Based reasoning (CBR). Penerapan CBR didukung dengan algoritma nearest neighbour untuk mencari kasus yang memiliki tingkat kemiripan yang tinggi. Pada pengujian dasar didapatkan hasil uji CBR dengan accuracy yang dirumuskan tertinggi dari 3 penguji yaitu 97,101%. Pada pengujian skenario AI sebagai wasit dianalisis lewat bidak yang bertabrakan dan memberikan keputusan yang tepat dalam menentukan kemenangan.Kata Kunci: The Battle of Honor, CBR, RBS, unity, AI