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• Create a new decision tree in Studio.
• Enter name and display name.

• Close the general tab.

• Start building the decision tree by selecting an attribute for the first question ( condition node ).

• For each possible answer you can select another node via the resource centric controls. 
• A decision tree must end with a result node (container, asset, tree or action).
  
  
• In order to be able to search for a decision tree you must enter one or more symptoms in the symptoms tab on the right.
• Save and close the decision tree when it is finished.

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• Create a new container.
• Enter the name.
• Select AQ_DecisionTreeSelector as the container type.
• Close the general tab.
• Enter the name of an attribute which holds the search query.

• Enter the names of the buttons that will be used to search for (matchbutton) and select (selectbutton) a decision tree.
• The AQ_DecisionTreeSelector uses a trigram matching algorithm to determine which decision tree symptom matches with the search query and calculates an overall score for each decision tree.

• Optionally you can enter a threshold ( percentage ) or a max number of results that are displayed.
  
  

• Save and close the container when it is finished.

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• Now that you have created all individual components you can create the following flow, to search for and execute a flow.
  
  
  
  
• Create a page containing the decision tree selector. In our example we named this page advice.
• Create a sub flow to evaluate the tree.
• In the sub flow create a page (on which the decision tree evaluator is placed) and a condition node to fetch the system.event.

• Save the flow.
• Test your decision tree in the runtime.

See also: Decisiontree example project.

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