Minimax Algorithm in Game Playing | Artificial Intelligence
Gate Smashers・10 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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