Minimax Algorithm is a artificial intelligence concept and a type of Search Algorithms. that enables Adversarial Search.
Semantic Classification
Content
Definition
Minimax is a decision-making algorithm used in two-player zero-sum games that determines the optimal move by minimizing the maximum possible loss. It works by recursively exploring the game tree, assuming the opponent will play optimally, and selecting moves that maximize the player’s minimum guaranteed outcome.
Algorithm Principles
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Maximizing player seeks highest score
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Minimizing player (opponent) seeks lowest score
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Recursive depth-first exploration
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Backpropagation of utility values
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Assumes perfect opponent play
Enhancements
Alpha-Beta Pruning:
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Eliminates branches that won’t affect final decision
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Reduces search space significantly
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Maintains identical results to full minimax
Iterative Deepening:
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Gradually increases search depth
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Provides time-bounded responses
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Improves move ordering
Transposition Tables:
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Cache evaluated positions
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Avoid redundant calculations
Applications
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Chess engines
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Checkers programs
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Tic-tac-toe solvers
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Connect Four
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General turn-based games
Limitations
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Exponential time complexity
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Requires complete game state information
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Computationally expensive for deep trees