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en:dydaktyka:ggp:game_tree_1 [2018/01/23 21:13] msl [Classical Game Theory Algorithms] |
en:dydaktyka:ggp:game_tree_1 [2019/01/03 23:00] msl |
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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> | ||
