Abstract
This paper introduces an effective algorithm designed for creating AI systems for the Hex board strategy game. The core algorithm, developed, employs the two-distance method for both board evaluation and for sorting of the moves. For empty board positions, the sum of two-distances from both ends is calculated to indicate the position’s weight and is used for sorting. Additionally, the Pattern Search algorithm enhances efficiency by prioritizing moves in crucial regions. The algorithm demonstrated consistent performance across various board sizes, including 7 × 7, 9 × 9, and 11 × 11. When implemented as an Android game, this algorithm maintained excellent performance in the given board sizes.
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Notes
- 1.
All figures in this manuscript are from the “Simple Hex Board game with AI”. Link: https://play.google.com/store/apps/details?id=com.SamgoGames.SimpleHex. The game can be installed and played on android based mobile devices with OS 7.0 and above.
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Acknowledgments
This work has been carried out as part of Summer Internship under the guidance of Mr. Naga Srinivas Vemuri, Google IT Services India Pvt Ltd, Hyderabad in his personal capacity. The author is deeply indebted to Dr. Naga Srinivas Vemuri, who is the primary developer of the code, for mentoring at every stage during the development of algorithm for building AI for the Hex board strategy game and for support during testing and performance evaluation.
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Inampudi, S.S. (2024). Enhancing Hex Strategy: AI Based Two-Distance Pruning Approach with Pattern-Enhanced Alpha-Beta Search. In: Garg, D., Rodrigues, J.J.P.C., Gupta, S.K., Cheng, X., Sarao, P., Patel, G.S. (eds) Advanced Computing. IACC 2023. Communications in Computer and Information Science, vol 2053. Springer, Cham. https://doi.org/10.1007/978-3-031-56700-1_36
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