b'Antoine Cully'

research

∙ 08/07/2023

QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Acceleration

QDax is an open-source library with a streamlined and modular API for Qu...

0 Félix Chalumeau, et al. ∙

research

∙ 06/20/2023

Deep perceptual hashing algorithms with hidden dual purpose: when client-side scanning does facial recognition

End-to-end encryption (E2EE) provides strong technical protections to in...

0 Shubham Jain, et al. ∙

research

∙ 06/08/2023

Gradient-Informed Quality Diversity for the Illumination of Discrete Spaces

Quality Diversity (QD) algorithms have been proposed to search for a lar...

0 Raphael Boige, et al. ∙

research

∙ 04/24/2023

Benchmark tasks for Quality-Diversity applied to Uncertain domains

While standard approaches to optimisation focus on producing a single hi...

0 Manon Flageat, et al. ∙

research

∙ 04/24/2023

Quality-Diversity Optimisation on a Physical Robot Through Dynamics-Aware and Reset-Free Learning

Learning algorithms, like Quality-Diversity (QD), can be used to acquire...

0 Simón C. Smith, et al. ∙

research

∙ 04/07/2023

Don't Bet on Luck Alone: Enhancing Behavioral Reproducibility of Quality-Diversity Solutions in Uncertain Domains

Quality-Diversity (QD) algorithms are designed to generate collections o...

0 Luca Grillotti, et al. ∙

research

∙ 03/10/2023

Understanding the Synergies between Quality-Diversity and Deep Reinforcement Learning

The synergies between Quality-Diversity (QD) and Deep Reinforcement Lear...

0 Bryan Lim, et al. ∙

research

∙ 03/10/2023

Multiple Hands Make Light Work: Enhancing Quality and Diversity using MAP-Elites with Multiple Parallel Evolution Strategies

With the development of hardware accelerators and their corresponding to...

0 Manon Flageat, et al. ∙

research

∙ 03/07/2023

MAP-Elites with Descriptor-Conditioned Gradients and Archive Distillation into a Single Policy

Quality-Diversity algorithms, such as MAP-Elites, are a branch of Evolut...

0 Maxence Faldor, et al. ∙

research

∙ 02/24/2023

Improving the Data Efficiency of Multi-Objective Quality-Diversity through Gradient Assistance and Crowding Exploration

Quality-Diversity (QD) algorithms have recently gained traction as optim...

0 Hannah Janmohamed, et al. ∙

research

∙ 02/01/2023

Uncertain Quality-Diversity: Evaluation methodology and new methods for Quality-Diversity in Uncertain Domains

Quality-Diversity optimisation (QD) has proven to yield promising result...

0 Manon Flageat, et al. ∙

research

∙ 11/24/2022

Assessing Quality-Diversity Neuro-Evolution Algorithms Performance in Hard Exploration Problems

A fascinating aspect of nature lies in its ability to produce a collecti...

0 Félix Chalumeau, et al. ∙

research

∙ 11/22/2022

Efficient Exploration using Model-Based Quality-Diversity with Gradients

Exploration is a key challenge in Reinforcement Learning, especially in ...

0 Bryan Lim, et al. ∙

research

∙ 11/22/2022

Discovering Unsupervised Behaviours from Full-State Trajectories

Improving open-ended learning capabilities is a promising approach to en...

0 Luca Grillotti, et al. ∙

research

∙ 11/09/2022

QuerySnout: Automating the Discovery of Attribute Inference Attacks against Query-Based Systems

Although query-based systems (QBS) have become one of the main solutions...

0 Ana-Maria Cretu, et al. ∙

research

∙ 11/04/2022

Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning

We present a Quality-Diversity benchmark suite for Deep Neuroevolution i...

0 Manon Flageat, et al. ∙

research

∙ 10/24/2022

Empirical analysis of PGA-MAP-Elites for Neuroevolution in Uncertain Domains

Quality-Diversity algorithms, among which MAP-Elites, have emerged as po...

0 Manon Flageat, et al. ∙

research

∙ 10/18/2022

Online Damage Recovery for Physical Robots with Hierarchical Quality-Diversity

In real-world environments, robots need to be resilient to damages and r...

2 Maxime Allard, et al. ∙

research

∙ 10/10/2022

Efficient Learning of Locomotion Skills through the Discovery of Diverse Environmental Trajectory Generator Priors

Data-driven learning based methods have recently been particularly succe...

0 Shikha Surana, et al. ∙

research

∙ 10/06/2022

Neuroevolution is a Competitive Alternative to Reinforcement Learning for Skill Discovery

Deep Reinforcement Learning (RL) has emerged as a powerful paradigm for ...

6 Félix Chalumeau, et al. ∙

research

∙ 04/21/2022

Relevance-guided Unsupervised Discovery of Abilities with Quality-Diversity Algorithms

Quality-Diversity algorithms provide efficient mechanisms to generate la...

0 Luca Grillotti, et al. ∙

research

∙ 04/12/2022

Hierarchical Quality-Diversity for Online Damage Recovery

Adaptation capabilities, like damage recovery, are crucial for the deplo...

9 Maxime Allard, et al. ∙

research

∙ 04/07/2022

Learning to Walk Autonomously via Reset-Free Quality-Diversity

Quality-Diversity (QD) algorithms can discover large and complex behavio...

0 Bryan Lim, et al. ∙

research

∙ 02/07/2022

Multi-Objective Quality Diversity Optimization

In this work, we consider the problem of Quality-Diversity (QD) optimiza...

0 Thomas Pierrot, et al. ∙

research

∙ 02/02/2022

Accelerated Quality-Diversity for Robotics through Massive Parallelism

Quality-Diversity (QD) algorithms are a well-known approach to generate ...

0 Bryan Lim, et al. ∙

research

∙ 09/16/2021

Dynamics-Aware Quality-Diversity for Efficient Learning of Skill Repertoires

Quality-Diversity (QD) algorithms are powerful exploration algorithms th...

0 Bryan Lim, et al. ∙

research

∙ 06/10/2021

Unsupervised Behaviour Discovery with Quality-Diversity Optimisation

Quality-Diversity algorithms refer to a class of evolutionary algorithms...

0 Luca Grillotti, et al. ∙

research

∙ 04/27/2021

Policy Manifold Search: Exploring the Manifold Hypothesis for Diversity-based Neuroevolution

Neuroevolution is an alternative to gradient-based optimisation that has...

0 Nemanja Rakicevic, et al. ∙

research

∙ 03/03/2021

On the Just-In-Time Discovery of Profit-Generating Transactions in DeFi Protocols

In this paper, we investigate two methods that allow us to automatically...

0 Liyi Zhou, et al. ∙

research

∙ 12/15/2020

Policy Manifold Search for Improving Diversity-based Neuroevolution

Diversity-based approaches have recently gained popularity as an alterna...

0 Nemanja Rakicevic, et al. ∙

research

∙ 12/08/2020

Quality-Diversity Optimization: a novel branch of stochastic optimization

Traditional optimization algorithms search for a single global optimum t...

17 Konstantinos Chatzilygeroudis, et al. ∙

research

∙ 09/17/2020

Competitiveness of MAP-Elites against Proximal Policy Optimization on locomotion tasks in deterministic simulations

The increasing importance of robots and automation creates a demand for ...

0 Szymon Brych, et al. ∙

research

∙ 07/10/2020

Multi-Emitter MAP-Elites: Improving quality, diversity and convergence speed with heterogeneous sets of emitters

Quality-Diversity (QD) optimisation is a new family of learning algorith...

0 Antoine Cully, et al. ∙

research

∙ 06/25/2020

Fast and stable MAP-Elites in noisy domains using deep grids

Quality-Diversity optimisation algorithms enable the evolution of collec...

4 Manon Flageat, et al. ∙

research

∙ 10/09/2019

Multimodal representation models for prediction and control from partial information

Similar to humans, robots benefit from interacting with their environmen...

0 Martina Zambelli, et al. ∙

research

∙ 05/28/2019

Autonomous skill discovery with Quality-Diversity and Unsupervised Descriptors

Quality-Diversity optimization is a new family of optimization algorithm...

0 Antoine Cully, et al. ∙

research

∙ 02/05/2019

AlphaStar: An Evolutionary Computation Perspective

In January 2019, DeepMind revealed AlphaStar to the world-the first arti...

6 Kai Arulkumaran, et al. ∙

research

∙ 04/19/2018

Hierarchical Behavioral Repertoires with Unsupervised Descriptors

Enabling artificial agents to automatically learn complex, versatile and...

0 Antoine Cully, et al. ∙

research

∙ 03/09/2018

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities

Biological evolution provides a creative fount of complex and subtle ada...

0 Joel Lehman, et al. ∙

research

∙ 05/12/2017

Quality and Diversity Optimization: A Unifying Modular Framework

The optimization of functions to find the best solution according to one...

0 Antoine Cully, et al. ∙

research

∙ 04/12/2017

MAGAN: Margin Adaptation for Generative Adversarial Networks

We propose the Margin Adaptation for Generative Adversarial Networks (MA...

0 Ruohan Wang, et al. ∙

research

∙ 11/22/2016

Limbo: A Fast and Flexible Library for Bayesian Optimization

Limbo is an open-source C++11 library for Bayesian optimization which is...

0 Antoine Cully, et al. ∙

research

∙ 10/05/2016

Towards semi-episodic learning for robot damage recovery

The recently introduced Intelligent Trial and Error algorithm (IT&E) ena...

0 Konstantinos Chatzilygeroudis, et al. ∙

research

∙ 07/13/2014

Robots that can adapt like animals

As robots leave the controlled environments of factories to autonomously...

0 Antoine Cully, et al. ∙

research

∙ 02/02/2013

Fast Damage Recovery in Robotics with the T-Resilience Algorithm

Damage recovery is critical for autonomous robots that need to operate f...

0 Sylvain Koos, et al. ∙

Antoine Cully

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