63 citations · 185 across the 37 of their papers we have counts for
41 papers
Quality-Diversity Search in Sound Generation: Investigating Innovation Engines for Audio Exploration
Björn Þór Jónsson, Çağrı Erdem, Stefano Fasciani +1
This study addresses the challenges composers and sound designers face in creating and refining tools to achieve their musical goals. Using evolutionary processes to promote divers…
Lamarckian Inheritance in Dynamic Environments: How Key Variables Affect Evolutionary Dynamics
K. Ege de Bruin, Kyrre Glette, Kai Olav Ellefsen
The co-optimization of a robot's body and brain presents a coupled challenge: the morphology constrains which control strategies are effective, while the control determines how wel…
Social Learning Strategies for Evolved Virtual Soft Robots
K. Ege de Bruin, Kyrre Glette, Kai Olav Ellefsen +2
Optimizing the body and brain of a robot is a coupled challenge: the morphology determines what control strategies are effective, while the control parameters influence how well th…
Integrating Sample Inheritance into Bayesian Optimization for Evolutionary Robotics
K. Ege de Bruin, Kyrre Glette, Kai Olav Ellefsen
In evolutionary robotics, robot morphologies are designed automatically using evolutionary algorithms. This creates a body-brain optimization problem, where both morphology and con…
Generational Replacement and Learning for High-Performing and Diverse Populations in Evolvable Robots
K. Ege de Bruin, Kyrre Glette, Kai Olav Ellefsen
Evolutionary Robotics offers the possibility to design robots to solve a specific task automatically by optimizing their morphology and control together. However, this co-optimizat…
Exploring Definitions of Quality and Diversity in Sonic Measurement Spaces
Björn Þór Jónsson, Çağrı Erdem, Stefano Fasciani +1
Digital sound synthesis presents the opportunity to explore vast parameter spaces containing millions of configurations. Quality diversity (QD) evolutionary algorithms offer a prom…
More complex environments may be required to discover benefits of lifetime learning in evolving robots
Ege de Bruin, Kyrre Glette, Kai Olav Ellefsen
It is well known that intra-life learning, defined as an additional controller optimization loop, is beneficial for evolving robot morphologies for locomotion. In this work, we inv…
Behaviour diversity in a walking and climbing centipede-like virtual creature
Emma Stensby Norstein, Kotaro Yasui, Takeshi Kano +2
Robot controllers are often optimised for a single robot in a single environment. This approach proves brittle, as such a controller will often fail to produce sensible behavior fo…
An Empirical Study on the Computation Budget of Co-Optimization of Robot Design and Control in Simulation
Etor Arza, Frank Veenstra, Tønnes F. Nygaard +1
The design (shape) of a robot is usually decided before the control is implemented. This might limit how well the design is adapted to a task, as the suitability of the design is g…
Design and Fabrication of Soft Locomotion Robots based on Spatial Compliant Mechanisms
Andrija Milojevic, Kyrre Glette
Soft robotics has emerged as a promising technology that holds great potential for various application areas. This is due to soft materials unique properties, including flexibility…
LVNS-RAVE: Diversified audio generation with RAVE and Latent Vector Novelty Search
Jinyue Guo, Anna-Maria Christodoulou, Balint Laczko +1
Evolutionary Algorithms and Generative Deep Learning have been two of the most powerful tools for sound generation tasks. However, they have limitations: Evolutionary Algorithms re…
Evolution of linkages for prototyping of linkage based robots
Emma Stensby Norstein, Kai Olav Ellefsen, Frank Veenstra +2
Prototyping robotic systems is a time consuming process. Computer aided design, however, might speed up the process significantly. Quality-diversity evolutionary approaches optimis…
Open-ended search for environments and adapted agents using MAP-Elites
Emma Stensby Norstein, Kai Olav Ellefsen, Kyrre Glette
Creatures in the real world constantly encounter new and diverse challenges they have never seen before. They will often need to adapt to some of these tasks and solve them in orde…
Central pattern generators evolved for real-time adaptation to rhythmic stimuli
Alex Szorkovszky, Frank Veenstra, Kyrre Glette
For a robot to be both autonomous and collaborative requires the ability to adapt its movement to a variety of external stimuli, whether these come from humans or other robots. Typ…
Centralized and Decentralized Control in Modular Robots and Their Effect on Morphology
Mia-Katrin Kvalsund, Kyrre Glette, Frank Veenstra
In Evolutionary Robotics, evolutionary algorithms are used to co-optimize morphology and control. However, co-optimizing leads to different challenges: How do you optimize a contro…
Rapid rhythmic entrainment in bio-inspired central pattern generators
Alex Szorkovszky, Frank Veenstra, Kyrre Glette
Entrainment of movement to a periodic stimulus is a characteristic intelligent behaviour in humans and an important goal for adaptive robotics. We demonstrate a quadruped central p…
Segmentation Consistency Training: Out-of-Distribution Generalization for Medical Image Segmentation
Birk Torpmann-Hagen, Vajira Thambawita, Kyrre Glette +2
Generalizability is seen as one of the major challenges in deep learning, in particular in the domain of medical imaging, where a change of hospital or in imaging routines can lead…
Complexity-based Encoded Information Quantification in Neurophysiological Recordings
Julian Fuhrer, Alejandro Blenkmann, Tor Endestad +2
Brain activity differs vastly between sleep, cognitive tasks, and action. Information theory is an appropriate concept to analytically quantify these brain states. Based on neuroph…
Co-optimising Robot Morphology and Controller in a Simulated Open-Ended Environment
Emma Hjellbrekke Stensby, Kai Olav Ellefsen, Kyrre Glette
Designing robots by hand can be costly and time consuming, especially if the robots have to be created with novel materials, or be robust to internal or external changes. In order…
MAP-Elites enables Powerful Stepping Stones and Diversity for Modular Robotics
Jørgen Nordmoen, Frank Veenstra, Kai Olav Ellefsen +1
In modular robotics, modules can be reconfigured to change the morphology of the robot, making it able to adapt for specific tasks. However, optimizing both the body and control is…
Quality and Diversity in Evolutionary Modular Robotics
Jørgen Nordmoen, Frank Veenstra, Kai Olav Ellefsen +1
In Evolutionary Robotics a population of solutions is evolved to optimize robots that solve a given task. However, in traditional Evolutionary Algorithms, the population of solutio…
A Framework for Automatic Behavior Generation in Multi-Function Swarms
Sondre A. Engebraaten, Jonas Moen, Oleg A. Yakimenko +1
Multi-function swarms are swarms that solve multiple tasks at once. For example, a quadcopter swarm could be tasked with exploring an area of interest while simultaneously function…
On Restricting Real-Valued Genotypes in Evolutionary Algorithms
Jørgen Nordmoen, Tønnes Frostad Nygaard, Eivind Samuelsen +1
Real-valued genotypes together with the variation operators, mutation and crossover, constitute some of the fundamental building blocks of Evolutionary Algorithms. Real-valued geno…
Real World Morphological Evolution is Feasible
Tonnes F. Nygaard, David Howard, Kyrre Glette
Evolutionary algorithms offer great promise for the automatic design of robot bodies, tailoring them to specific environments or tasks. Most research is done on simplified models o…