Interactive visualizer to facilitate game designers understand machine learning

Kavish Harchandani; Rajiv Nagesh; Roshan Badarkhe; Tannay Bagga; Nitesh Chaudhari

Interactive visualizer to facilitate game designers understand machine learning

June 2021

Vol-7, Issue-3

Paper ID: 14470

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Engineering

Keywords

Machine Learning Sudoku AI Game Designing Interactive Visualizer

Abstract

Solving Sudoku has been a challenge for the past decade. The aim was to develop a highly efficient algorithm to reduce computer time and use less memory space. This article develops an algorithm for solving Sudoku puzzle using a method, called a pencil and paper algorithm. This algorithm is similar to human methods, that is, it describes how a person tries to solve a puzzle using certain techniques. Our desire is to use a pencil and paper algorithm using these methods. There are currently variations of Sudoku such as 4X4 grids, 9X9 grids and 16X16 grids. This work focuses on the classic and standard Sudoku of the 9X9 board, then a comparison between the paper and pencil method and the Brute force algorithm. I hope, by doing this work we can answer the following questions: How is the pencil and paper algorithm different from the Brute force algorithm? Which of them works best? Is it possible to make these algorithms work better?

License

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Author Information

#	Name	Institute / Affiliation
1	Kavish Harchandani	Dr. D.Y. Patil College Of Engineering
2	Rajiv Nagesh	Dr. D.Y. Patil College Of Engineering
3	Roshan Badarkhe	Dr. D.Y. Patil College Of Engineering
4	Tannay Bagga	Dr. D.Y. Patil College Of Engineering
5	Nitesh Chaudhari	Dr. D.Y. Patil College Of Engineering

How to Cite

Use the following formats to cite this article in your research.

APA Style

Harchandani, Kavish, Nagesh, Rajiv, Badarkhe, Roshan, Bagga, Tannay, & Chaudhari, Nitesh (2021). Interactive visualizer to facilitate game designers understand machine learning. International Journal of Advance Research and Innovative Ideas In Education, 7(3), 1727-1730.

MLA Style

Harchandani, Kavish, et al. "Interactive visualizer to facilitate game designers understand machine learning." International Journal of Advance Research and Innovative Ideas In Education, vol. 7, no. 3, 2021, pp. 1727-1730.

IEEE Style

Kavish Harchandani, Rajiv Nagesh, Roshan Badarkhe, Tannay Bagga, and Nitesh Chaudhari, "Interactive visualizer to facilitate game designers understand machine learning," International Journal of Advance Research and Innovative Ideas In Education, vol. 7, no. 3, pp. 1727-1730, 2021.

Vancouver Style

Harchandani Kavish, Nagesh Rajiv, Badarkhe Roshan, Bagga Tannay, Chaudhari Nitesh. Interactive visualizer to facilitate game designers understand machine learning. International Journal of Advance Research and Innovative Ideas In Education. 2021;7(3):1727-1730.

Harvard Style

Harchandani, Kavish, Nagesh, Rajiv, Badarkhe, Roshan, Bagga, Tannay, & Chaudhari, Nitesh (2021) 'Interactive visualizer to facilitate game designers understand machine learning', International Journal of Advance Research and Innovative Ideas In Education, 7(3), pp. 1727-1730.

Chicago Style

Harchandani, Kavish, et al. "Interactive visualizer to facilitate game designers understand machine learning." International Journal of Advance Research and Innovative Ideas In Education 7, no. 3 (2021): 1727-1730.

Turabian Style

Harchandani, Kavish, et al. "Interactive visualizer to facilitate game designers understand machine learning." International Journal of Advance Research and Innovative Ideas In Education 7, no. 3 (2021): 1727-1730.