3 citations · 4 across the 6 of their papers we have counts for
6 papers
A comparison of controller architectures and learning mechanisms for arbitrary robot morphologies
Jie Luo, Jakub Tomczak, Karine Miras +1
The main question this paper addresses is: What combination of a robot controller and a learning method should be used, if the morphology of the learning robot is not known in adva…
Lamarck's Revenge: Inheritance of Learned Traits Can Make Robot Evolution Better
Jie Luo, Karine Miras, Jakub Tomczak +1
Evolutionary robot systems offer two principal advantages: an advanced way of developing robots through evolutionary optimization and a special research platform to conduct what-if…
A Comparative Study of Brain Reproduction Methods for Morphologically Evolving Robots
Jie Luo, Carlo Longhi, Agoston E. Eiben
In the most extensive robot evolution systems, both the bodies and the brains of the robots undergo evolution and the brains of 'infant' robots are also optimized by a learning pro…
Environment induced emergence of collective behaviour in evolving swarms with limited sensing
Fuda van Diggelen, Jie Luo, Tugay Alperen Karagüzel +3
Designing controllers for robot swarms is challenging, because human developers have typically no good understanding of the link between the details of a controller that governs in…
The Effects of Learning in Morphologically Evolving Robot Systems
Jie Luo, Aart Stuurman, Jakub M. Tomczak +2
Simultaneously evolving morphologies (bodies) and controllers (brains) of robots can cause a mismatch between the inherited body and brain in the offspring. To mitigate this proble…
Gait-learning with morphologically evolving robots generated by L-system
Jie Luo, Daan Zeeuwe, Agoston E. Eiben
When controllers (brains) and morphologies (bodies) of robots simultaneously evolve, this can lead to a problem, namely the brain & body mismatch problem. In this research, we prop…