Jacqueline Heinerman
Papers
7
Total Citations
94
H-Index
5
About
Jacqueline Heinerman is a pioneering researcher in evolutionary robotics and adaptive multi-robot systems, with a focus on how robots can autonomously evolve both their control systems and physical morphologies. Her most influential work, "Evolution, Individual Learning, and Social Learning in a Swarm of Real Robots" (29 citations), introduced a novel adaptive framework that combines three learning mechanisms—evolution, individual learning, and social learning—in physical Thymio II robots, distinguishing between inheritable and learnable traits. In her proof-of-concept study "A Robotic Ecosystem with Evolvable Minds and Bodies" (21 citations), she demonstrated a groundbreaking system where robots could self-reproduce, enabling online evolution of both controllers and body plans. Her research on "Three-fold Adaptivity in Groups of Robots" (18 citations) further extended these ideas to e-puck robots, showing how real-time adaptation can improve swarm performance. Heinerman's work has fundamentally advanced the field of embodied evolution, providing experimental evidence that social learning can accelerate learning speed and improve task performance in robotic collectives. Her contributions are essential reading for anyone interested in autonomous adaptive systems, swarm robotics, and the future of self-reproducing machines.
Research Focus
Key Achievements
Top Papers
- 1
- 2A robotic ecosystem with evolvable minds and bodies21 citations · 2014
- 3Three-fold Adaptivity in Groups of Robots18 citations · 2015
- 4On-line Evolution of Foraging Behaviour in a Population of Real Robots17 citations · 2016
- 5
- 6Is social learning more than parameter tuning?2 citations · 2017
- 7Can social learning increase learning speed, performance or both?2 citations · 2017