Minimax Algorithm in Game Playing | Artificial Intelligence
Gate Smashers・2 minutes read
Minimax Algorithm chooses the best move by calculating values from root to leaf levels, aiming to maximize utility for Max and minimize for Min, with a time complexity of O(B^D). However, Minimax is not ideal for games like Chess with many possible moves due to its impracticality with large game trees.
Insights
- Minimax Algorithm is a strategic approach in game playing where players aim to maximize their utility while minimizing the opponent's utility, achieved by selecting moves based on calculated values from root to leaf levels.
- The time complexity of Minimax Algorithm, crucial for evaluating its efficiency, is determined by the branching factor (B) and depth (D) of the game tree, impacting its feasibility for games with a large number of possible moves like Chess.
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Recent questions
What is the Minimax Algorithm?
A backtracking algorithm for game playing.
Why is Breadth-First Search not used in game playing?
Allows undoing moves, unsuitable for sequential game moves.
What is the best move strategy in game playing?
Maximizing utility for oneself while minimizing opponent's utility.
What are the objectives of Max and Min players in Minimax Algorithm?
Max player maximizes utility, Min player minimizes opponent's utility.
What is the time complexity of the Minimax Algorithm?
Order of B^D, where B is branching factor and D is depth.
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Summary
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"Minimax Algorithm: Game Strategy for Decision Making"
- Minimax Algorithm is a backtracking algorithm where values are calculated from root to leaf levels, and the best move is chosen by propagating these values.
- Breadth-First Search is not used in game playing as it allows undoing moves, which is not suitable for sequential game moves.
- Best move strategy involves maximizing utility for oneself while minimizing the opponent's utility.
- In Minimax, Max player aims to maximize utility, while Min player aims to minimize the opponent's utility.
- The algorithm involves choosing the maximum utility at each level for Max and the minimum utility for Min.
- The time complexity of Minimax Algorithm is Order of B^D, where B is the branching factor and D is the depth.
- Minimax Algorithm is not suitable for games with a large number of possible moves and choices, like Chess, due to the vast game tree, making it impractical for such games.
