Abstract Evolutionary Ensemble Learning (EEL) provides a general approach for scaling
evolutionary learning algorithms to increasingly complex tasks. This is generally achieved …

This article comparatively tests three cooperative co-evolution methods for automated
controller design in simulated robot teams. Collective Neuro-Evolution (CONE) co-evolves …

Cooperative coevolutionary algorithms (CCEAs) rely on multiple coevolving populations for
the evolution of solutions composed of coadapted components. CCEAs enable, for instance …

Cooperative coevolution is an approach for evolving solutions composed of coadapted
components. Previous research has shown, however, that cooperative coevolutionary …

We propose Hyb-CCEA, a cooperative coevolutionary algorithm for the evolution of
genetically heterogeneous multiagent teams. The proposed approach extends the …

Cooperative coevolution algorithms (CCEAs) facilitate the evolution of heterogeneous,
cooperating multiagent systems. Such algorithms are, however, subject to inherent …

The potential of cooperative coevolutionary algorithms (CCEAs) as a tool for evolving control
for heterogeneous multirobot teams has been shown in several previous works. The vast …

The objective of this work is to analyze embodied evolution based algorithms in coordinated
multi-robot tasks that require specialization. This type of algorithm performs a Darwinian …

Abstract This article evaluates Collective Neuro-Evolution (CONE), a cooperative co-
evolutionary method for solving collective behavior tasks and increasing task performance …

Heterogeneous multirobot systems have shown significant potential in many applications.
Cooperative coevolutionary algorithms (CCEAs) represent a promising approach to …