963 citations · 1k across the 8 of their papers we have counts for
6 papers
An Online Data-Driven Emergency-Response Method for Autonomous Agents in Unforeseen Situations
Glenn Maguire, Nicholas Ketz, Praveen Pilly +1
Reinforcement learning agents perform well when presented with inputs within the distribution of those encountered during training. However, they are unable to respond effectively…
Safety-Aware Robot Damage Recovery Using Constrained Bayesian Optimization and Simulated Priors
Vaios Papaspyros, Konstantinos Chatzilygeroudis, Vassilis Vassiliades +1
The recently introduced Intelligent Trial-and-Error (IT&E) algorithm showed that robots can adapt to damage in a matter of a few trials. The success of this algorithm relies on two…
Limbo: A Fast and Flexible Library for Bayesian Optimization
Antoine Cully, Konstantinos Chatzilygeroudis, Federico Allocati +1
Limbo is an open-source C++11 library for Bayesian optimization which is designed to be both highly flexible and very fast. It can be used to optimize functions for which the gradi…
Towards semi-episodic learning for robot damage recovery
Konstantinos Chatzilygeroudis, Antoine Cully, Jean-Baptiste Mouret
The recently introduced Intelligent Trial and Error algorithm (IT\&E) enables robots to creatively adapt to damage in a matter of minutes by combining an off-line evolutionary algo…
Evolvability signatures of generative encodings: beyond standard performance benchmarks
Danesh Tarapore, Jean-Baptiste Mouret
Evolutionary robotics is a promising approach to autonomously synthesize machines with abilities that resemble those of animals, but the field suffers from a lack of strong foundat…
Robots that can adapt like animals
Antoine Cully, Jeff Clune, Danesh Tarapore +1
As robots leave the controlled environments of factories to autonomously function in more complex, natural environments, they will have to respond to the inevitable fact that they…