Evolving Small Neurocontrollers with Self-Organized Compact Encoding

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...

Evolving Neurocontrollers in the RoboCup Domain

On ‘Parts’ and ‘Wholes’ of Adaptive Behavior: Functional Modularity and Diachronic Structure in Recurrent Neural Robot Controllers

This paper discusses the issue of self-organized modularity for adaptive robot behavior. In particular we introduce the concept of functional modularity through diachronic structure in recurrent neural robot control mechanisms. We demonstrate how behavioral adaptivity through quasi-modularity at a functional level can be realized in monolithic recurrent neurocontrollers through context-dependen...

Self-organized Stochastic Tipping in Slow-fast Dynamical Systems

Polyhomeostatic adaption occurs when evolving systems try to achieve a target distribution function for certain dynamical parameters, a generalization of the notion of homeostasis. Here we consider a single rate encoding leaky integrator neuron model driven by white noise, adapting slowly its internal parameters, the threshold and the gain, in order to achieve a given target distribution for it...

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...