mlsanityData to 7 Oct 2026

Benchmarking Quality-Diversity Algorithms on Neuroevolution for Reinforcement Learning

arXiv 2211.02193 ↗First posted 4 Nov 2022cs.NE cs.AI cs.LGcited by 10

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Abstract (arXiv)

We present a Quality-Diversity benchmark suite for Deep Neuroevolution in Reinforcement Learning domains for robot control. The suite includes the definition of tasks, environments, behavioral descriptors, and fitness. We specify different benchmarks based on the complexity of both the task and the agent controlled by a deep neural network. The benchmark uses standard Quality-Diversity metrics, including coverage, QD-score, maximum fitness, and an archive profile metric to quantify the relation between coverage and fitness. We also present how to quantify the robustness of the solutions with respect to environmental stochasticity by introducing corrected versions of the same metrics. We believe that our benchmark is a valuable tool for the community to compare and improve their findings. The source code is available online: https://github.com/adaptive-intelligent-robotics/QDax

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 21 of its 30 references that are in the map. First posted on arXiv 4 Nov 2022.

Builds on

21 of 30 references.

References · 21

  1. 2014Microsoft COCO: Common Objects in Contextcited by 17,498
  2. 2017Evolution Strategies as a Scalable Alternative to Reinforcement Learningcited by 555
  3. 2015Illuminating search spaces by mapping elitescited by 406
  4. 2021Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulationcited by 375
  5. 2020First return, then explorecited by 256
  6. 2014Robots that can adapt like animalscited by 203
  7. 2017Deep Neuroevolution: Genetic Algorithms Are a Competitive Alternative for Training Deep Neural Networks for Reinforcement Learningcited by 148
  8. 2017Quality and Diversity Optimization: A Unifying Modular Frameworkcited by 111
  9. 2021Differentiable Quality Diversitycited by 71
  10. 2016Using Centroidal Voronoi Tessellations to Scale Up the Multi-dimensional Archive of Phenotypic Elites Algorithmcited by 65
  11. 2020Quality-Diversity Optimization: a novel branch of stochastic optimizationcited by 59
  12. 2020Diversity Policy Gradient for Sample Efficient Quality-Diversity Optimizationcited by 53
9 more
  1. 2020Illuminating Mario Scenes in the Latent Space of a Generative Adversarial Networkcited by 51
  2. 2018Data-Efficient Design Exploration through Surrogate-Assisted Illuminationcited by 38
  3. 2020Scaling MAP-Elites to Deep Neuroevolutioncited by 38
  4. 2022Approximating Gradients for Differentiable Quality Diversity in Reinforcement Learningcited by 37
  5. 2019Mapping Hearthstone Deck Spaces through MAP-Elites with Sliding Boundariescited by 32
  6. 2016Reset-free Trial-and-Error Learning for Robot Damage Recoverycited by 24
  7. 2019Deep Neuroevolution of Recurrent and Discrete World Modelscited by 22
  8. 2022Accelerated Quality-Diversity through Massive Parallelismcited by 14
  9. 2020Fast and stable MAP-Elites in noisy domains using deep gridscited by 13

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 6; 2024: 1; 2025: 2; 2026: 1.

10 papers.

  1. 2023pyribs: A Bare-Bones Python Library for Quality Diversity Optimizationcited by 29
  2. 2023QDax: A Library for Quality-Diversity and Population-based Algorithms with Hardware Accelerationcited by 16
  3. 2024Quality-Diversity Actor-Critic: Learning High-Performing and Diverse Behaviors via Value and Successor Features Criticscited by 13
  4. 2023The Quality-Diversity Transformer: Generating Behavior-Conditioned Trajectories with Decision Transformerscited by 10
  5. 2025Quality-Diversity Red-Teaming: Automated Generation of High-Quality and Diverse Attackers for Large Language Modelscited by 8
  6. 2023Synergizing Quality-Diversity with Descriptor-Conditioned Reinforcement Learningcited by 6
  7. 2023Understanding the Synergies between Quality-Diversity and Deep Reinforcement Learningcited by 5
  8. 2023Don't Bet on Luck Alone: Enhancing Behavioral Reproducibility of Quality-Diversity Solutions in Uncertain Domainscited by 3
  9. 2026DEI: Diversity in Evolutionary Inference for Quality-Diversity Searchcited by 1
  10. 2025Scaling Policy Gradient Quality-Diversity with Massive Parallelization via Behavioral Variationscited by 0