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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...
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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...
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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...
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04/24/2023
Benchmark tasks for Quality-Diversity applied to Uncertain domains
While standard approaches to optimisation focus on producing a single hi...
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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...
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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...
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03/10/2023
Understanding the Synergies between Quality-Diversity and Deep Reinforcement Learning
The synergies between Quality-Diversity (QD) and Deep Reinforcement Lear...
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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...
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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...
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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...
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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...
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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...
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11/22/2022
Efficient Exploration using Model-Based Quality-Diversity with Gradients
Exploration is a key challenge in Reinforcement Learning, especially in ...
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11/22/2022
Discovering Unsupervised Behaviours from Full-State Trajectories
Improving open-ended learning capabilities is a promising approach to en...
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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...
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11/04/2022
Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning
We present a Quality-Diversity benchmark suite for Deep Neuroevolution i...
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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...
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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...
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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...
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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 ...
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04/21/2022
Relevance-guided Unsupervised Discovery of Abilities with Quality-Diversity Algorithms
Quality-Diversity algorithms provide efficient mechanisms to generate la...
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04/12/2022
Hierarchical Quality-Diversity for Online Damage Recovery
Adaptation capabilities, like damage recovery, are crucial for the deplo...
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04/07/2022
Learning to Walk Autonomously via Reset-Free Quality-Diversity
Quality-Diversity (QD) algorithms can discover large and complex behavio...
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02/07/2022
Multi-Objective Quality Diversity Optimization
In this work, we consider the problem of Quality-Diversity (QD) optimiza...
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02/02/2022
Accelerated Quality-Diversity for Robotics through Massive Parallelism
Quality-Diversity (QD) algorithms are a well-known approach to generate ...
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09/16/2021
Dynamics-Aware Quality-Diversity for Efficient Learning of Skill Repertoires
Quality-Diversity (QD) algorithms are powerful exploration algorithms th...
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06/10/2021
Unsupervised Behaviour Discovery with Quality-Diversity Optimisation
Quality-Diversity algorithms refer to a class of evolutionary algorithms...
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04/27/2021
Policy Manifold Search: Exploring the Manifold Hypothesis for Diversity-based Neuroevolution
Neuroevolution is an alternative to gradient-based optimisation that has...
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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...
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12/15/2020
Policy Manifold Search for Improving Diversity-based Neuroevolution
Diversity-based approaches have recently gained popularity as an alterna...
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12/08/2020
Quality-Diversity Optimization: a novel branch of stochastic optimization
Traditional optimization algorithms search for a single global optimum t...
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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 ...
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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...
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06/25/2020
Fast and stable MAP-Elites in noisy domains using deep grids
Quality-Diversity optimisation algorithms enable the evolution of collec...
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10/09/2019
Multimodal representation models for prediction and control from partial information
Similar to humans, robots benefit from interacting with their environmen...
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05/28/2019
Autonomous skill discovery with Quality-Diversity and Unsupervised Descriptors
Quality-Diversity optimization is a new family of optimization algorithm...
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02/05/2019
AlphaStar: An Evolutionary Computation Perspective
In January 2019, DeepMind revealed AlphaStar to the world-the first arti...
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04/19/2018
Hierarchical Behavioral Repertoires with Unsupervised Descriptors
Enabling artificial agents to automatically learn complex, versatile and...
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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...
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05/12/2017
Quality and Diversity Optimization: A Unifying Modular Framework
The optimization of functions to find the best solution according to one...
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04/12/2017
MAGAN: Margin Adaptation for Generative Adversarial Networks
We propose the Margin Adaptation for Generative Adversarial Networks (MA...
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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...
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10/05/2016
Towards semi-episodic learning for robot damage recovery
The recently introduced Intelligent Trial and Error algorithm (IT&E) ena...
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07/13/2014
Robots that can adapt like animals
As robots leave the controlled environments of factories to autonomously...
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02/02/2013
