A Simple Neural Network for the Control of a Six-Legged Walking System

Abstract

All behaving systems—whether living or artificial—can be placed along a continuum spanning three types. One type comprises strictly sensory or data-driven, feedforward systems, such as simple reflex machines. The extant input determines the output. Although the internal state of such systems might be changed by learning, the system at any moment can be regarded as having a static world model. The other two types of systems have a form of world model that can be used to make predictions concerning future states of the world. Two levels may be distinguished. One is the type of system possessing an internal world model which is “manipulable” in the sense that the internal world model can be cut off from the sensory input and the motor output and then used to mentally “play” with different possibilities. Such a model could be used for thinking, for reflecting and—when connected to a value system—for decision making.