Aliased from Behavior Trees
From the description of Behaviour Trees on Wikipedia:
A behavior tree is a mathematical model
of plan execution used in computer science , robotics , control systems and video games. They describe switchings between a finite set of tasks in a modular
fashion. Their strength comes from their ability to create very complex tasks composed of simple tasks, without worrying how the simple tasks are implemented. Behavior trees present some similarities to hierarchical state machines
with the key difference that the main building block of a behavior is a
task rather than a state. Its ease of human understanding make behavior
trees less error prone and very popular in the game developer
community. Behavior trees have been shown to generalize several other
control architectures. Mathematically, they are directed acyclic graphs .
of plan execution used in computer science , robotics , control systems and video games. They describe switchings between a finite set of tasks in a modular
fashion. Their strength comes from their ability to create very complex tasks composed of simple tasks, without worrying how the simple tasks are implemented. Behavior trees present some similarities to hierarchical state machines
with the key difference that the main building block of a behavior is a
task rather than a state. Its ease of human understanding make behavior
trees less error prone and very popular in the game developer
community. Behavior trees have been shown to generalize several other
control architectures. Mathematically, they are directed acyclic graphs .
References#
- Behavior tree (artificial intelligence, robotics and control) on Wikipedia
- Behavior trees for AI: How they work
An introduction to Behavior Trees, with examples and in-depth descriptions, as well as some tips on creating powerful expressive trees. by Chris Simpson - Behavior Tree Engine (in Python) on github
- How Behavior Trees Modularize Hybrid ControlSystems and Generalize Sequential BehaviorCompositions, the Subsumption Architecture, and Decision Trees, Michele Colledanchise and Petter Ögren (PDF)