Answers.Body: <p>It's not too clear from your question what you mean, but I guess this is not even originally a question coming from you, so I'll suppose you cannot give more information</p>
  <p>In any case, if the result of your minimax algorithm is a path of the game tree, aka a Nash Equilibrium, then the problem is that there might be more than one Nash Equilibrium. If the result of the minimax is a whole strategy, then it implies that you have found a SubGame Nash Equilibrium, and by definition you will maximize your minimum gain</p>
  <p>This is assuming you are dealing with a perfect information game</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-04-26T21:47:47.313Z
Answers.LastActivityDate: 2024-04-26T21:47:47.313Z
Answers.UserDisplayName: Alberto
Body: <blockquote>
  <p>MAX and MIN apply the minimax algorithm each time before making their move, searching to some predefined
  depth. Imagine, however, that the MAX player applies the minimax algorithm only once, at the beginning of the
  game, and then uses the obtained minimax values for all his future moves. In what case would MAX player
  implemented in this way surely maximize his minimum gain?</p>
  <p>A There is no guarantee that such a player would maximize his minimum gain</p>
  <p>B If he has reached all final states of the game when calculating the minimax-value</p>
  <p>C If MAX’s heuristic is more informed than MIN’s heuristics</p>
  <p>D If he uses a heuristic that is identical to that of MIN player</p>
  </blockquote>
  <p>Can someone explain why the answer is A and not B?</p>
  
Tags: <minimax><zero-sum-games>
Title: Can MAX ensure maximum minimum gain by using minimax once at game start?
UserDisplayName: I love Java
ThreadText: # Can MAX ensure maximum minimum gain by using minimax once at game start?
  
  (Asked by: username_0 on 2024-04-26)
  
  > MAX and MIN apply the minimax algorithm each time before making their move, searching to some predefined
  > depth. Imagine, however, that the MAX player applies the minimax algorithm only once, at the beginning of the
  > game, and then uses the obtained minimax values for all his future moves. In what case would MAX player
  > implemented in this way surely maximize his minimum gain?
  >
  > A There is no guarantee that such a player would maximize his minimum gain
  >
  > B If he has reached all final states of the game when calculating the minimax-value
  >
  > C If MAX’s heuristic is more informed than MIN’s heuristics
  >
  > D If he uses a heuristic that is identical to that of MIN player
  
  Can someone explain why the answer is A and not B?
  
  **Tags:** minimax, zero-sum-games
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2024-04-26. Score: 0
  
  It's not too clear from your question what you mean, but I guess this is not even originally a question coming from you, so I'll suppose you cannot give more information
  
  In any case, if the result of your minimax algorithm is a path of the game tree, aka a Nash Equilibrium, then the problem is that there might be more than one Nash Equilibrium. If the result of the minimax is a whole strategy, then it implies that you have found a SubGame Nash Equilibrium, and by definition you will maximize your minimum gain
  
  This is assuming you are dealing with a perfect information game
  
  
  ---
  
  