Using Assembler Encoding to build neuro-controllers for a team of autonomous underwater vehicles

The paper compares a neuro-evolutionary metod called Assembler Encoding with two other methods from the area of neuro–evolution. As a testbed for the methods a variant of the predator–prey problem with Autonomous Underwater Vehicles (AUV) operating in an environment with the sea current was used. In the experiments, the task of vehicles–predators controlled with evolutionary neural networks was to capture a vehicle–prey behaving according to a simple deterministic strategy. All the experiments were carried out in simulation, and in order to simplify calculations in the two–dimensional environment – AUVs moved on a horizontal surface under the water.