6'YA 6 TAHTA ÜZERİNDE AT KAPLAMA PROBLEMİNİ ÇÖZMEK İÇİN DENETİMSİZ MAKİNE ÖĞRENME ALGORİTMASI

Modülerlik, çizgelerden bilgi çıkarmak için, çok kullanılan bir makine öğrenimi algoritmasıdır. Modülerlik, özünde, ele alınan ağı daha küçük kümelere böler. Oluşturan kümeler, aynı kümedeki düğümler arasındaki paylaşılan özellikleri vurgular. Bu çalışmada 6×6 at çizgesini modülerlik yöntemiyle analiz ederek 6 At Kaplama Probleminin (6-AKP) çözümlerini elde ettik. Araştırmamız 0,1 ile 2,0 arasındaki çözünürlükler için değişmektedir. Çözünürlük 1,2 için bulunan maksimum modülerlik puanı 0,318'dir. 0,3 ve 0,4 olmak üzere çözünürlükler, tüm çözümleri 8 at ile tanımladı. Ayrıca, 0,2 çözünürlükler için 8 at ve 0,2, 0,3 ve 0,4 çözünürlükler için 9, 10, 11, 12, 13 at ile bazı çözümler elde edilmektedir. Ayrıca, çözünürlük 0,3, 6-AKP çözümlerini bulmak için en verimli çözünürlüktür. Ayrıca, analizlerimiz gösterdi ki 0,2 çözünürlüğü, 6-AKP'nin 195 çözümünü daha fazla çözüm bulmak için en iyi çözünürlüktür. Son olarak, modülerlik yöntemi, 2253 çözüm arasından 0,5 çözünürlük için 61'den, 0,2 çözünürlük için 195'e kadar olan çözümleri çıkarıyor.

Anahtar Kelimeler:

At çizgesi, modülerlik, At Kaplama Problemi, Makine öğrenmesi

UNSUPERVISED MACHINE LEARNING ALGORITHM TO SOLVE KNIGHT COVERING PROBLEM FOR 6 BY 6 BOARD

Modularity is a well-known method as a machine-learning algorithm to extract information from graphs. The modularity, in essence, divides the considered network into smaller clusters. The extracted clusters highlight the shared properties between the nodes in the same cluster. In the present study, we analyze the 6×6 knight graph by modularity method to obtain 6 Knight Covering Problem (6-KCP) solutions. Our investigation is ranged for the resolutions from 0.1 to 2.0. The maximum modularity score is 0.318 found for resolution 1.2. The resolutions, namely 0.3 and 0.4, identified all solutions, by 8 knights. Moreover, some solutions are obtained by 8 knights for the resolutions 0.2 and by 9, 10, 11, 12, 13 knights for the resolutions 0.2, 0.3, and 0.4. Moreover, resolution 0.3 is the most efficient resolution to find 6-KCP solutions. Also, within our analysis, resolution 0.2 is the best resolution to find more solutions, 195 solutions of 6-KCP. Lastly, the modularity method extracts the solutions from 61, for resolution 0.5, to 195, for resolution 0.2, out of 2253 solutions.

Keywords:

Knight graph, modularity, Knight Covering Problem, Machine learning,

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