While evolutionary computation and evolutionary robotics take inspiration from nature, they
have long focused mainly on problems of performance optimization. Yet evolution in nature …

Many fields use search algorithms, which automatically explore a search space to find high-
performing solutions: chemists search through the space of molecules to discover new …

We present the Evolved Grasping Analysis Dataset (EGAD), comprising over 2000
generated objects aimed at training and evaluating robotic visual grasp detection …

The evolution of task-oriented control for robots with complex locomotor systems is currently
out of reach for traditional evolutionary computation techniques, as the coordination of a …

Novelty search is a tool in evolutionary and swarm robotics for maintaining the diversity of
population needed for continuous robotic operation. It enables nature-inspired algorithms to …

Novelty Search is an exploration algorithm driven by the novelty of a behavior. The same
individual evaluated at different generations has different fitness values. The corresponding …

Procedurally generated video game content has the potential to drastically reduce the
content creation budget of game developers and large studios. However, adoption is …

Performing Reinforcement Learning in sparse rewards settings, with very little prior
knowledge, is a challenging problem since there is no signal to properly guide the learning …

A long-term vision of evolutionary robotics is a technology enabling the evolution of entire
autonomous robotic ecosystems that live and work for long periods in challenging and …

In the past few years, a considerable amount of research has been dedicated to the
exploitation of previous learning experiences and the design of Few-shot and Meta Learning …