The general algorithm applied on a game tree for making a decision of win/lose is called the Minimax algorithm. Here are the steps:

1. Generate the entire game tree starting from the current position of the game all the way up to the terminal states, which represent game outcomes.

2. Apply the utility function to each terminal state to get its value. The utility function is designed to measure the desirability of the game outcomes.

3. Use the Minimax decision rule to calculate the utility of the intermediate states. If the player is a maximizing player, the utility of the state is the maximum utility of the successor states. If the player is a minimizing player, the utility of the state is the minimum utility of the successor states.

4. Choose the move that leads to the state with the highest utility.

This algorithm assumes perfect play from both players, meaning that it assumes that both players will always make the best possible move.

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The general algorithm applied on a game tree for making a decision of win/lose is called the Minimax algorithm. Here are the steps:

1. Generate the entire game tree starting from the current position of the game all the way up to the terminal states, which represent game outcomes.

2. Apply the utility function to each terminal state to get its value. The utility function is designed to measure the desirability of the game outcomes.

3. Use the Minimax decision rule to calculate the utility of the intermediate states. If the player is a maximizing player, the utility of the state is the maximum utility of the successor states. If the player is a minimizing player, the utility of the state is the minimum utility of the successor states.

4. Choose the move that leads to the state with the highest utility.

This algorithm assumes perfect play from both players, meaning that it assumes that both players will always make the best possible move.

Knowee AI · Accepted Answer

The general algorithm applied on a game tree for making a decision of win/lose is called the Minimax algorithm. Here are the steps:

1. Generate the entire game tree starting from the current position of the game all the way up to the terminal states, which represent game outcomes.

2. Apply the utility function to each terminal state to get its value. The utility function is designed to measure the desirability of the game outcomes.

3. Use the Minimax decision rule to calculate the utility of the intermediate states. If the player is a maximizing player, the utility of the state is the maximum utility of the successor states. If the player is a minimizing player, the utility of the state is the minimum utility of the successor states.

4. Choose the move that leads to the state with the highest utility.

This algorithm assumes perfect play from both players, meaning that it assumes that both players will always make the best possible move.

General algorithm applied on game tree for making decision of win/lose is

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