Observational emergence of a fuzzy controller evolved by genetic algorithm
Abstract
Explaining emergence is a difficult work, such that there are many arguments on what it is or how it can be explained. Nonetheless, it is frequently referred to in many fields, such as behavior-based robotics, artificial life and complex systems, without any formal definition. In this paper, we develop a fuzzy logic controller for a simulated mobile robot with a genetic algorithm and analyze the behavior of the controller from the perspective of observational emergence. The analysis shows that the fuzzy logic controller has acquired emergent behavior through the interactions of the underlying fuzzy rules.
Authors: Seung‐Ik Lee, Sung-Bae Cho
Published in: Congress on Evolutionary Computation (2002)