Biologically Inspired Agent System Based on Spiking Neural Network

Abstract

The paper presents an architecture of a biologically inspired agent. Its physical body is described first. The agent’s movement is directly controlled by Spiking Neural Network. To achieve this goal, the network is trained by a genetic algorithm. The agents move in a 3D physical environment. Their main goal is to effectively translocate themselves using a virtual body structure and muscles. This approach is inspired by a biological assumptions, where the neural network receives signals from sensors and directly controls the muscles. The application of Spiking Neural Network needs a suitable signal encoding method, which is also described. The system is flexible and it allows to create agents with various body structures and different neural controllers. Experiments presented in the paper refer to a simple snake-like creature. The effectiveness of controllers based on a standard threshold network and the spiking one are compared.