Repo: clean up and flatten structures for Search lectures (#357)

follow-up to #352 In Search hatten wir noch ein tiefe Unterstruktur, die zu einem relativ verschachtelten Menü führt. Dieser PR korrgiert dies.
Artificial-Intelligence-HSBI-TDU · Aug 22, 2024 · 6d44065 · 6d44065
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diff --git a/lecture/searching/informed/images/.noslides → lecture/searching/images/.noslides b/lecture/searching/informed/images/.noslides → lecture/searching/images/.noslides
diff --git a/...e/searching/informed/images/challenge.png → lecture/searching/images/challenge.png b/...e/searching/informed/images/challenge.png → lecture/searching/images/challenge.png
diff --git a/...hing/informed/images/challenges_robby.png → ...ure/searching/images/challenges_robby.png b/...hing/informed/images/challenges_robby.png → ...ure/searching/images/challenges_robby.png
diff --git a/lecture/searching/informed/images/graph.png → lecture/searching/images/graph.png b/lecture/searching/informed/images/graph.png → lecture/searching/images/graph.png
diff --git a/.../searching/local/images/hill-climbing.png → lecture/searching/images/hill-climbing.png b/.../searching/local/images/hill-climbing.png → lecture/searching/images/hill-climbing.png
diff --git a/...ure/searching/uninformed/images/scene.png → lecture/searching/images/scene.png b/...ure/searching/uninformed/images/scene.png → lecture/searching/images/scene.png
diff --git a/...g/local/images/screenshot_stundenplan.png → ...arching/images/screenshot_stundenplan.png b/...g/local/images/screenshot_stundenplan.png → ...arching/images/screenshot_stundenplan.png
diff --git a/...arching/informed/images/tafelbeispiel.png → lecture/searching/images/tafelbeispiel.png b/...arching/informed/images/tafelbeispiel.png → lecture/searching/images/tafelbeispiel.png
diff --git a/lecture/searching/informed/readme.md b/lecture/searching/informed/readme.md
diff --git a/lecture/searching/local/images/.noslides b/lecture/searching/local/images/.noslides
diff --git a/lecture/searching/local/images/challenge.png b/lecture/searching/local/images/challenge.png
diff --git a/lecture/searching/local/images/graph.png b/lecture/searching/local/images/graph.png
diff --git a/lecture/searching/local/images/tafelbeispiel.png b/lecture/searching/local/images/tafelbeispiel.png
diff --git a/lecture/searching/local/readme.md b/lecture/searching/local/readme.md
diff --git a/lecture/searching/readme.md b/lecture/searching/readme.md
@@ -7,6 +7,10 @@ title: "Suche"
 Problemlösen durch Suche im Problemgraphen. Aus den Basisalgorithmen Tree-Search und Graph-Search
 entstehen je nach verwendeter Datenstruktur und nach betrachteten Kosten unterschiedliche Suchalgorithmen.
 
+-   Uninformierte Suche: ... jeder Schritt "kostet" gleich viel: nur die Anzahl der Schritte zählt ...
+-   Informierte Suche: ... Einsatz einer Kostenfunktion ...
+-   Lokale Suche: ... das Ziel ist im Weg ...
+
 
 `{{< children showhidden="true" >}}`{=markdown}
 

diff --git a/lecture/searching/uninformed/search1-dfs.md → lecture/searching/search1-dfs.md b/lecture/searching/uninformed/search1-dfs.md → lecture/searching/search1-dfs.md
diff --git a/lecture/searching/uninformed/search2-bfs.md → lecture/searching/search2-bfs.md b/lecture/searching/uninformed/search2-bfs.md → lecture/searching/search2-bfs.md
diff --git a/...rching/informed/search3-branchandbound.md → lecture/searching/search3-branchandbound.md b/...rching/informed/search3-branchandbound.md → lecture/searching/search3-branchandbound.md
diff --git a/...e/searching/informed/search4-bestfirst.md → lecture/searching/search4-bestfirst.md b/...e/searching/informed/search4-bestfirst.md → lecture/searching/search4-bestfirst.md
@@ -34,7 +34,7 @@ challenges: |
     ![](https://upload.wikimedia.org/wikipedia/commons/thumb/a/ad/MapGermanyGraph.svg/476px-MapGermanyGraph.svg.png)
     Quelle: [MapGermanyGraph.svg](https://commons.wikimedia.org/wiki/File:MapGermanyGraph.svg) by [Regnaron](https://de.wikipedia.org/wiki/Benutzer:Regnaron) and [Jahobr](https://commons.wikimedia.org/wiki/User:Jahobr) on Wikimedia Commons ([Public Domain](https://en.wikipedia.org/wiki/en:public_domain))
 
-    ![](https://raw.githubusercontent.com/Artificial-Intelligence-HSBI-TDU/KI-Vorlesung/master/lecture/searching/informed/images/challenge.png)
+    ![](https://raw.githubusercontent.com/Artificial-Intelligence-HSBI-TDU/KI-Vorlesung/master/lecture/searching/images/challenge.png)
 
     Finden Sie mit der **Best-First-Suche** jeweils einen Weg von Würzburg nach München. Vergleichen Sie das Ergebnis mit der Gradienten-Suche.
 ---

diff --git a/lecture/searching/informed/search5-astar.md → lecture/searching/search5-astar.md b/lecture/searching/informed/search5-astar.md → lecture/searching/search5-astar.md
@@ -41,7 +41,7 @@ challenges: |
 
     Betrachten Sie folgendes Problem:
 
-    ![](https://raw.githubusercontent.com/Artificial-Intelligence-HSBI-TDU/KI-Vorlesung/master/lecture/searching/informed/images/challenges_robby.png)
+    ![](https://raw.githubusercontent.com/Artificial-Intelligence-HSBI-TDU/KI-Vorlesung/master/lecture/searching/images/challenges_robby.png)
 
     Dargestellt ist eine typische Büroumgebung mit verschiedenen Räumen und einem Flur. Die Pfeile in den Durchgängen geben an, in welche Richtung der jeweilige Durchgang durchschritten werden darf. Die Werte an den Pfeilen geben die Kosten für den Übergang von einem Raum in den anderen an.
 

diff --git a/lecture/searching/local/search6-gradient.md → lecture/searching/search6-gradient.md b/lecture/searching/local/search6-gradient.md → lecture/searching/search6-gradient.md
@@ -34,7 +34,7 @@ challenges: |
     ![](https://upload.wikimedia.org/wikipedia/commons/thumb/a/ad/MapGermanyGraph.svg/476px-MapGermanyGraph.svg.png)
     Quelle: [MapGermanyGraph.svg](https://commons.wikimedia.org/wiki/File:MapGermanyGraph.svg) by [Regnaron](https://de.wikipedia.org/wiki/Benutzer:Regnaron) and [Jahobr](https://commons.wikimedia.org/wiki/User:Jahobr) on Wikimedia Commons ([Public Domain](https://en.wikipedia.org/wiki/en:public_domain))
 
-    ![](https://raw.githubusercontent.com/Artificial-Intelligence-HSBI-TDU/KI-Vorlesung/master/lecture/searching/local/images/challenge.png)
+    ![](https://raw.githubusercontent.com/Artificial-Intelligence-HSBI-TDU/KI-Vorlesung/master/lecture/searching/images/challenge.png)
 
     Finden Sie mit der **Gradienten-Suche** jeweils einen Weg von Würzburg nach München. Vergleichen Sie das Ergebnis mit der Best-First-Suche.
 ---

diff --git a/lecture/searching/local/search7-annealing.md → lecture/searching/search7-annealing.md b/lecture/searching/local/search7-annealing.md → lecture/searching/search7-annealing.md
diff --git a/lecture/searching/uninformed/images/.noslides b/lecture/searching/uninformed/images/.noslides
diff --git a/lecture/searching/uninformed/images/graph.png b/lecture/searching/uninformed/images/graph.png
diff --git a/lecture/searching/uninformed/images/tafelbeispiel.png b/lecture/searching/uninformed/images/tafelbeispiel.png
diff --git a/lecture/searching/uninformed/readme.md b/lecture/searching/uninformed/readme.md
diff --git a/readme.md b/readme.md
@@ -256,13 +256,13 @@ Hier finden Sie einen abonnierbaren [Google Kalender] mit allen Terminen der Ver
 [Einführung KI]: lecture/intro/intro1-overview.md
 [Problemlösen]: lecture/intro/intro2-problemsolving.md
 
-[Tiefensuche]: lecture/searching/uninformed/search1-dfs.md
-[Breitensuche]: lecture/searching/uninformed/search2-bfs.md
-[Branch-and-Bound]: lecture/searching/informed/search3-branchandbound.md
-[Best First]: lecture/searching/informed/search4-bestfirst.md
-[A-Stern]: lecture//searching/informed/search5-astar.md
-[Gradientensuche]: lecture/searching/local/search6-gradient.md
-[Simulated Annealing]: lecture/searching/local/search7-annealing.md
+[Tiefensuche]: lecture/searching/search1-dfs.md
+[Breitensuche]: lecture/searching/search2-bfs.md
+[Branch-and-Bound]: lecture/searching/search3-branchandbound.md
+[Best First]: lecture/searching/search4-bestfirst.md
+[A-Stern]: lecture//searching/search5-astar.md
+[Gradientensuche]: lecture/searching/search6-gradient.md
+[Simulated Annealing]: lecture/searching/search7-annealing.md
 
 [Intro EA/GA]: lecture/ea/ea1-intro.md
 [Genetische Algorithmen]: lecture/ea/ea2-ga.md