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Quality diversity: A new frontier for evolutionary computation
While evolutionary computation and evolutionary robotics take inspiration from nature, they
have long focused mainly on problems of performance optimization. Yet, evolution in nature …
have long focused mainly on problems of performance optimization. Yet, evolution in nature …
Illuminating search spaces by map** elites
Evolution of repertoire-based control for robots with complex locomotor systems
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 …
out of reach for traditional evolutionary computation techniques, as the coordination of a …
Novelty search for global optimization
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 …
population needed for continuous robotic operation. It enables nature-inspired algorithms to …
LLM2FEA: Discover Novel Designs with Generative Evolutionary Multitasking
The rapid research and development of generative artificial intelligence has enabled the
generation of high-quality images, text, and 3D models from text prompts. This advancement …
generation of high-quality images, text, and 3D models from text prompts. This advancement …
Novelty search: a theoretical perspective
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 …
individual evaluated at different generations has different fitness values. The corresponding …
Procedural content generation using neuroevolution and novelty search for diverse video game levels
Procedurally generated video game content has the potential to drastically reduce the
content creation budget of game developers and large studios. However, adoption is …
content creation budget of game developers and large studios. However, adoption is …
Efficient novelty search through deep reinforcement learning
Novelty search, which was inspired by the nature that evolves creatures with diversity, has
shown great potential in solving reinforcement learning (RL) tasks with sparse and …
shown great potential in solving reinforcement learning (RL) tasks with sparse and …
Few-shot quality-diversity optimization
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 …
exploitation of previous learning experiences and the design of Few-shot and Meta Learning …