Industrial Engineering Graduate Seminar
CANDIDATE: Aliyu (Saif) Vandana
DEGREE SOUGHT: MASc
DATE: 3/26/2025
TIME: 4:00PM
PLACE: Room 2101 CEI
TITLE: Strategic Decision-Making in Racing Kings: AI Implementation using Minimax with Alpha-Beta Pruning
Abstract
Artificial intelligence (AI) has revolutionized strategic decision-making in board games, with algorithms such as Minimax and Alpha-Beta Pruning playing a crucial role in chess AI development. This study presents the implementation of an AI agent for Racing Kings, a chess variant with unique objectives and movement rules, using Python. The AI utilizes the Minimax algorithm to evaluate optimal moves, enhanced by Alpha-Beta Pruning to improve computational efficiency. The program was developed to simulate intelligent gameplay, incorporating heuristic evaluation functions tailored to Racing Kings' distinctive gameplay dynamics. Performance analysis was conducted by testing the AI against various difficulty levels and evaluating key metrics such as search depth, computation time, and decision quality. Results demonstrate the effectiveness of the implemented AI in making strategic moves while highlighting the computational challenges posed by the game's complexity. This work contributes to AI-driven game playing by providing a structured approach to adapting traditional chess algorithms to unconventional game variants, offering insights for further optimization and potential applications in game AI research.