Diederik M. Roijers

About

Diederik M. Roijers is a leading researcher in artificial intelligence, with a primary focus on reinforcement learning, evolutionary robotics, and Bayesian optimization. His work bridges the gap between learning algorithms and real-world robotic systems, particularly in the context of modular robots with evolvable morphologies. Roijers has made significant contributions to understanding how robots can learn directed locomotion—moving in a specific target direction—rather than just undirected gaits, a problem he has tackled across multiple studies (with papers accumulating 26, 24, and 14 citations). His 2021 paper on "Time efficiency in optimization with a Bayesian-Evolutionary algorithm" (65 citations) stands out as his most cited work, demonstrating how to combine Bayesian Optimization with evolutionary strategies to reduce computational overhead in generate-and-test search. Additionally, his 2018 paper on "Open-Ended Learning" (61 citations) provides a conceptual framework for reinforcement learning in unknown domains, moving beyond traditional Markov Decision Processes. Roijers has also addressed practical challenges in robotics, such as real-time vision on low-performance hardware (20 citations), and explored the relative importance of robot bodies versus brains in evolutionary design. His research is highly influential for students and researchers working at the intersection of AI, robotics, and optimization.

Research Focus

Key Achievements

Top Papers

1. 1
   Time efficiency in optimization with a bayesian-Evolutionary algorithm

   65 citations · 2021
2. 2
   Open-Ended Learning: A Conceptual Framework Based on Representational Redescription

   61 citations · 2018
3. 3
   Learning directed locomotion in modular robots with evolvable morphologies

   26 citations · 2021
4. 4
   Directed Locomotion for Modular Robots with Evolvable Morphologies

   24 citations · 2018
5. 5
   Real-Time Robot Vision on Low-Performance Computing Hardware

   20 citations · 2018
6. 6
   Learning Directed Locomotion in Modular Robots with Evolvable Morphologies

   14 citations · 2020
7. 7
   Time Efficiency in Optimization with a Bayesian-Evolutionary Algorithm

   11 citations · 2020
8. 8
   Analysing the Relative Importance of Robot Brains and Bodies

   4 citations · 2018

Key Collaborators

Contact & Links