963 citations · 3.1k across the 34 of their papers we have counts for
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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…
Using Centroidal Voronoi Tessellations to Scale Up the Multi-dimensional Archive of Phenotypic Elites Algorithm
Vassilis Vassiliades, Konstantinos Chatzilygeroudis, Jean-Baptiste Mouret
The recently introduced Multi-dimensional Archive of Phenotypic Elites (MAP-Elites) is an evolutionary algorithm capable of producing a large archive of diverse, high-performing so…
Reset-free Trial-and-Error Learning for Robot Damage Recovery
Konstantinos Chatzilygeroudis, Vassilis Vassiliades, Jean-Baptiste Mouret
The high probability of hardware failures prevents many advanced robots (e.g., legged robots) from being confidently deployed in real-world situations (e.g., post-disaster rescue).…