This article is concerned with a fixed-size population of autonomous agents facing unknown,
possibly changing, environments. The motivation is to design an embodied evolutionary …

Online evolution gives robots the capacity to learn new tasks and to adapt to changing
environmental conditions during task execution. Previous approaches to online evolution of …

Due to their high strength-to-weight ratio, robustness and deformability, tensegrity structures
are an appealing platform for the emerging field of soft robotics, with applications ranging …

In this chapter, we survey the most significant applications of EML to robotics. We first
highlight the salient characteristics of the field in terms of what can be optimized and with …

Inspired by animals' ability to learn and adapt to changes in their environment during life,
hybrid evolutionary algorithms have been developed and successfully applied in a number …

Finding optimal traffic light timings at road intersections is a mandatory step for urban
planners wishing to achieve a sustainable mobility in modern cities. Increasing congestion …

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 …

Evolutionary algorithms have previously shown promise in generating controllers for legged
robots. Multiple evaluations across many evolutionary generations are typically required …

We describe an experimental platform that uses differential evolution to automatically
discover high-performance multirotor controllers. All control parameters are tuned …

This paper proposes a simple method based on a novel use of elitism to increase the
population size of artificial creatures while minimizing evaluation cost. This can contribute to …