Evolving Structure and Function of Neurocontrollers

Evolving Neurocontrollers in the RoboCup Domain

Potentials of Evolving Linear Models in Tracking Control Design for Nonlinear Variable Structure Systems

Evolving models have found applications in many real world systems. In this paper, potentials of the Evolving Linear Models (ELMs) in tracking control design for nonlinear variable structure systems are introduced. At first, an ELM is introduced as a dynamic single input, single output (SISO) linear model whose parameters as well as dynamic orders of input and output signals can change through ...

Evolving Small Neurocontrollers with Self-Organized Compact Encoding

This article presents a novel method for the evolution of artificial autonomous agents with small neurocontrollers. It is based on adaptive, self-organized compact genotypic encoding (SOCE) generating the phenotypic synaptic weights of the agent's neurocontroller. SOCE implements a parallel evolutionary search for neurocontroller solutions in a dynamically varying and reduced subspace of the or...

Evolutionary neurocontrollers for autonomous mobile robots

In this article we describe a methodology for evolving neurocontrollers of autonomous mobile robots without human intervention. The presentation, which spans from technological and methodological issues to several experimental results on evolution of physical mobile robots, covers both previous and recent work in the attempt to provide a unified picture within which the reader can compare the e...

Evolving a neurocontroller through a process of embryogeny

We introduce a model of cellular growth that generates neurocontrollers capable of guiding simple simulated agents in a harvesting task. The morphogenesis of the neurocontroller is itself controlled by an evolved artificial neural network. The neural network operates only on local variables and chemical concentrations and is thought as a flexible model of a gene regulatory system and cell metab...