Answers.Body: <p>I think you are looking at it from the wrong direction, min-max is just a planning algorithm, decision strategy, in the sense that you are describing other algorithms/methods it does not have a category. For example, you have negamax algorithm which is in a sense the same thing the Monte Carlo Search Tree is to Monte Carlo. Min-max category is game theory really.</p>
  
  <p>Now you should be thinking about RL algorithms in another way, and this is taxonomy:</p>
  
  <p><a href="https://i.sstatic.net/lAhlN.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/lAhlN.png" alt=""></a></p>
  
  <p>So if you think about methods, you mentioned, let's put them in the right place:</p>
  
  <ul>
  <li>TD methods in general - model free</li>
  <li>Monte Carlo methods - model free</li>
  <li>MinMax - model-based (that could be discussed but it definitely needs access to a world model)</li>
  </ul>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2020-05-14T21:19:50.093Z
Answers.LastActivityDate: 2020-05-14T21:19:50.093Z
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Body: <p>Q-learning is a temporal-difference method and Monte Carlo tree search is a Monte Carlo method. In what category is MiniMax?</p>
  
Tags: <reinforcement-learning><definitions><minimax><monte-carlo-methods><temporal-difference-methods>
Title: In what RL algorithm category is MiniMax?
UserDisplayName: mason7663
ThreadText: # In what RL algorithm category is MiniMax?
  
  (Asked by: username_0 on 2020-05-14)
  
  Q-learning is a temporal-difference method and Monte Carlo tree search is a Monte Carlo method. In what category is MiniMax?
  
  **Tags:** reinforcement-learning, definitions, minimax, monte-carlo-methods, temporal-difference-methods
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2020-05-14. Score: 4
  
  I think you are looking at it from the wrong direction, min-max is just a planning algorithm, decision strategy, in the sense that you are describing other algorithms/methods it does not have a category. For example, you have negamax algorithm which is in a sense the same thing the Monte Carlo Search Tree is to Monte Carlo. Min-max category is game theory really.
  
  Now you should be thinking about RL algorithms in another way, and this is taxonomy:
  
  [![](https://i.sstatic.net/lAhlN.png)](https://i.sstatic.net/lAhlN.png)
  
  So if you think about methods, you mentioned, let's put them in the right place:
  
  * TD methods in general - model free
  * Monte Carlo methods - model free
  * MinMax - model-based (that could be discussed but it definitely needs access to a world model)
  
  
  ---
  
  