124 citations · 350 across the 23 of their papers we have counts for
6 papers · 1 filter
Quality-Diversity Optimisation on a Physical Robot Through Dynamics-Aware and Reset-Free Learning
Simón C. Smith, Bryan Lim, Hannah Janmohamed +1
Learning algorithms, like Quality-Diversity (QD), can be used to acquire repertoires of diverse robotics skills. This learning is commonly done via computer simulation due to the l…
Online Damage Recovery for Physical Robots with Hierarchical Quality-Diversity
Maxime Allard, Simón C. Smith, Konstantinos Chatzilygeroudis +2
In real-world environments, robots need to be resilient to damages and robust to unforeseen scenarios. Quality-Diversity (QD) algorithms have been successfully used to make robots…
Hierarchical Quality-Diversity for Online Damage Recovery
Maxime Allard, Simón C. Smith, Konstantinos Chatzilygeroudis +1
Adaptation capabilities, like damage recovery, are crucial for the deployment of robots in complex environments. Several works have demonstrated that using repertoires of pre-train…
Multimodal representation models for prediction and control from partial information
Martina Zambelli, Antoine Cully, Yiannis Demiris
Similar to humans, robots benefit from interacting with their environment through a number of different sensor modalities, such as vision, touch, sound. However, learning from diff…
Autonomous skill discovery with Quality-Diversity and Unsupervised Descriptors
Antoine Cully
Quality-Diversity optimization is a new family of optimization algorithms that, instead of searching for a single optimal solution to solving a task, searches for a large collectio…
Hierarchical Behavioral Repertoires with Unsupervised Descriptors
Antoine Cully, Yiannis Demiris
Enabling artificial agents to automatically learn complex, versatile and high-performing behaviors is a long-lasting challenge. This paper presents a step in this direction with hi…