Optimization and Comparative Analysis of Game Theory Algorithms used in Zero-Sum Games
Rimjhim Sinha, Shivani Rajput, Omkar Singh, Saneet Saluja, Vitthal Sadashiv Gutte · 2023
This study is focused on the notion of game theory and how well various algorithms work on zero-sum games. We have used measures like optimality, and time and space complexity to compare Minimax and Negamax algorithms. Minimax and Negamax are game theory algorithms used in zero-sum games to find the optimal moves for all the players in the game. We have also studied the implications and benefits of using the Alpha-Beta pruning on both Minimax and Negamax algorithms. Alpha-beta pruning is an optimization technique that reduces the complexity of these algorithms by pruning nodes that do not contribute significantly in devising the optimal strategy. The main objective of this study is to know how well these two algorithms work when applied to zero-sum games, their optimizations, and their limitations and find the one that works the best for zero-sum games.