Learning Behavior Trees with Genetic Programming in Unpredictable Environments
Matteo Iovino Jonathan Styrud Pietro Falco Christian Smith Matteo Iovino Jonathan Styrud Pietro Falco Christian Smith
Modern industrial applications require robots to operate in unpredictable environments, and programs to be created with a minimal effort, to accommodate frequent changes to the task. Here, we show that genetic programming can be effectively used to learn the structure of a behavior tree (BT) to solve a robotic task in an unpredictable environment. We propose to use a simple simulator for learning,...