5-2 Final Project Milestone Three Proposed Changes

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Jan 9, 2024

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5-2 Final Project Milestone Three: Proposed Changes Yasin Yusuf 12/1/2023 Proposed AI Solution: After weeks of playing against the AI, in my opinion it is to simple to defeat after experiencing the logic behind its moves. Using Minimax(with Alpha-Beta pruning) search tree is one way to potentially solve this issue. which, according to what I understand is the search tree component of the minimax method. It will make the AI more challenging because it will be able to find more tricky moves during the game. Determine which possible logical systems could be applied to solve the AI problem. How are these relevant to the game? Alpha-beta pruning's fundamental principle is that a move is dropped once it is determined to be ineffective, and no further resources are used to determine just how ineffective it actually is. This is comparable to branch and bound search, where partially explored pathways are dropped when they are determined to be less than ideal. As things stand, the AI is programmed to read off a list of movements and doesn't actually see moves ahead of time; instead, it plays only when the situation calls for it. As opposed to simply going through a list and making moves based on who has more pieces, this more sophisticated

approach would consider each action and base the next move accordingly. In order for the AI to plan and prepare to attack or counter, it can be helpful to have the AI value each position and move made by the opponent. This way, the AI can learn more about what the opponent will do next. The minimax method's implementation is significantly more sophisticated than the current heuristic approach.

Lucci, Stephen, and Danny Kopec. Artificial Intelligence in the 21st Century [OP] , Mercury Learning & Information, 2015. ProQuest Ebook Central ,

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