From 351d25d429d6794f9d8e51069ed9edfe648ae40a Mon Sep 17 00:00:00 2001
From: Maximo Comperatore <131000419+pyoneerC@users.noreply.github.com>
Date: Fri, 30 Aug 2024 05:42:04 -0300
Subject: [PATCH] descision trees (#6788)

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 .../content/decision-tree-learning@sz1047M8_kScjth84yPwU.md | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/src/data/roadmaps/game-developer/content/decision-tree-learning@sz1047M8_kScjth84yPwU.md b/src/data/roadmaps/game-developer/content/decision-tree-learning@sz1047M8_kScjth84yPwU.md
index a8ff937a3..cfedff5a7 100644
--- a/src/data/roadmaps/game-developer/content/decision-tree-learning@sz1047M8_kScjth84yPwU.md
+++ b/src/data/roadmaps/game-developer/content/decision-tree-learning@sz1047M8_kScjth84yPwU.md
@@ -1,3 +1,7 @@
 # Decision Tree Learning
 
-`Decision Tree Learning` is an important concept in game development, particularly in the development of artificial intelligence for game characters. It is a kind of machine learning method that is based on using decision tree models to predict or classify information. A decision tree is a flowchart-like model, where each internal node denotes a test on an attribute, each branch represents an outcome of that test, and each leaf node holds a class label (decision made after testing all attributes). By applying decision tree learning models, computer-controlled characters can make decisions based on different conditions or states. They play a key role in creating complex and interactive gameplay experiences, by enabling game characters to adapt to the player's actions and the ever-changing game environment.
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+`Decision Tree Learning` is an important concept in game development, particularly in the development of artificial intelligence for game characters. It is a kind of machine learning method that is based on using decision tree models to predict or classify information. A decision tree is a flowchart-like model, where each internal node denotes a test on an attribute, each branch represents an outcome of that test, and each leaf node holds a class label (decision made after testing all attributes). By applying decision tree learning models, computer-controlled characters can make decisions based on different conditions or states. They play a key role in creating complex and interactive gameplay experiences, by enabling game characters to adapt to the player's actions and the ever-changing game environment.
+
+Visit the following resources to learn more:
+
+- [@video@Decision trees - A friendly introduction](https://www.youtube.com/watch?v=HkyWAhr9v8g)
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