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en:dydaktyka:ggp:game_tree_1 [2018/01/23 13:36]
msl [Ćwiczenia]
en:dydaktyka:ggp:game_tree_1 [2019/01/03 22:00]
msl
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 {{ :​pl:​dydaktyka:​ggp:​tic-tac-toe-tree.png?​500 | }} {{ :​pl:​dydaktyka:​ggp:​tic-tac-toe-tree.png?​500 | }}
  
-We will use the '​ggp-base'​ framework, [[en:​dydaktyka:​ggp:​gdl|introduced together with the gdl language]].+We will use the '​ggp-base'​ framework, [[en:​dydaktyka:​ggp:​gdl#validation|introduced together with the gdl language]].
  
 ===== First Legal Move ===== ===== First Legal Move =====
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   - bonus assignments   - bonus assignments
     - add possibility to cinstraint the search depth (several moves look-ahead) --- it's a classical method to scale the AI power. Why this method may be better than the timeout? ​       ​     - add possibility to cinstraint the search depth (several moves look-ahead) --- it's a classical method to scale the AI power. Why this method may be better than the timeout? ​       ​
-    - implement the  [[http://sandbox.thimbleby.net/algorithms/doku.php?​id=minimax_search|NegaMax algorithm]]+    - implement the  [[https://​thimbleby.gitlab.io/algorithm-wiki-site/​wiki/​minimax_search/|NegaMax algorithm]]
    
  
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 Ending of [[https://​www.youtube.com/​watch?​v=Ewh-rF7KSEg|the video]] shows an example of the Alpha-Beta pruning. Ending of [[https://​www.youtube.com/​watch?​v=Ewh-rF7KSEg|the video]] shows an example of the Alpha-Beta pruning.
  
-<WRAP center round tip 60%>[[http://will.thimbleby.net/algorithms/doku.php?​id=minimax_search_with_alpha-beta_pruning|Interactive Visualization of the algorithm]].+<WRAP center round tip 60%>[[https://​thimbleby.gitlab.io/algorithm-wiki-site/​wiki/​minimax_search_with_alpha-beta_pruning/|Interactive Visualization of the algorithm]].
 </​WRAP>​ </​WRAP>​
    
en/dydaktyka/ggp/game_tree_1.txt · Last modified: 2019/01/03 22:00 by msl
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