Adversarial search algorithms
The search algorithms like DFS, BFS, and A* can be well-suited for single-agent environments where there is no direct competition or conflict between multiple agents. These algorithms are suitable for finding an optimal solution in such scenarios. On the other hand, in zero-sum games where two players compete directly against each other, adversarial search algorithms like Minmax and Alpha-Beta pruning are more appropriate since these algorithms can determine the best course of action for each player in zero-sum games.
Adversarial Search Algorithms
Adversarial search algorithms are the backbone of strategic decision-making in artificial intelligence, it enables the agents to navigate competitive scenarios effectively. This article offers concise yet comprehensive advantages of these algorithms from their foundational principles to practical applications. Let’s uncover the strategies that drive intelligent gameplay in adversarial environments.
Table of Content
- What is an Adversarial search?
- Adversarial search algorithms
- Minimax algorithm
- Alpha-beta pruning
- Adversarial search algorithm Implementations using Connect-4 Game
- Applications of adversarial search algorithms
- Conclusion
- FAQ’s on Adversarial search algorithms
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