7 papers · 1 filter
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…
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…
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…