Minimax Algorithm in Artificial Intelligence | Minimax Algorithm Explained | AI Tutorial|Simplilearn

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This video on "Minimax Algorithm in Artificial Intelligence" will briefly explain the Minimax Algorithm. The "Minimax Algorithm Explained" video will cover the Topics like the Algorithm's pseudo-code and demonstrate an algorithm's working with an example. The minimax algorithm is commonly used in two-player games like chess, checkers, and tic-tac-toe.

The "Minimax Algorithm in Artificial Intelligence" will cover the following topics:

✅00:00-Minimax Algorithm in Artificial Intelligence

✅00:52-Introduction to Minimax algorithm in AI

✅01:32-Properties of the minimax algorithm

✅02:14-Pseudo-code of Minimax algorithm

✅03:46-Working of minimax algorithm in AI- With Examples

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The Minimax algorithm's main goal is to choose the best move for the player currently making a move, assuming that the opposing player would also play optimally, minimizing the player's maximum possible loss.

The Minimax Algorithm is a popular decision-making algorithm in Artificial Intelligence used in game theory and decision theory. It is a backtracking algorithm that uses the depth-first-search concept to traverse all the nodes of a tree. It tries out different possibilities in a systematic manner and backtracks when a solution is not found.

✅Some of the properties of the minimax algorithm are:

-Completeness

-Optimal

-Time complexity

-Space complexity

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