Poster Title

An Artificial Intelligence Approach to Mancala

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Department

Computing

Abstract

Through the study of popular games such as Chess and Go, countless artificial intelligence (AI) research has been conducted in an attempt to create algorithms equipped for adversarial search problems. However, there are still a plethora of avenues that offer insight into further development. Mancala is traditionally a two-player board game that originated in the East and offers a unique opponent-based playing experience. This thesis not only attempts to create a competitive AI algorithm for mancala games by analyzing the performance of several different algorithms on a number of mancala variations, but it also attempts to extract applications that may have relevance to other “game-solving” AI problems.

Thank you for your interest in the Artificial Intelligence Approach to Mancala. We regret this session is no longer available. We invite you to engage with some of our other students during this time.

Acknowledgments

Advisor: Rodney Summerscales

Thesis Record URL

https://digitalcommons.andrews.edu/honors/257/

Session

Department of Computing

Event Website

https://www.andrews.edu/services/research/research_events/conferences/urs_honors_poster_symposium/index.html

Start Date

3-26-2021 1:40 PM

End Date

3-26-2021 2:00 PM

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COinS
 
Mar 26th, 1:40 PM Mar 26th, 2:00 PM

An Artificial Intelligence Approach to Mancala

Through the study of popular games such as Chess and Go, countless artificial intelligence (AI) research has been conducted in an attempt to create algorithms equipped for adversarial search problems. However, there are still a plethora of avenues that offer insight into further development. Mancala is traditionally a two-player board game that originated in the East and offers a unique opponent-based playing experience. This thesis not only attempts to create a competitive AI algorithm for mancala games by analyzing the performance of several different algorithms on a number of mancala variations, but it also attempts to extract applications that may have relevance to other “game-solving” AI problems.

Thank you for your interest in the Artificial Intelligence Approach to Mancala. We regret this session is no longer available. We invite you to engage with some of our other students during this time.

https://digitalcommons.andrews.edu/honors-undergraduate-poster-symposium/2021/symposium/17