mlsanityData to 7 Oct 2026

MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning

arXiv 2310.08252 ↗First posted 12 Oct 2023cs.LG cs.AI cs.NEcited by 35

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Abstract (arXiv)

Recently, Meta-Black-Box Optimization with Reinforcement Learning (MetaBBO-RL) has showcased the power of leveraging RL at the meta-level to mitigate manual fine-tuning of low-level black-box optimizers. However, this field is hindered by the lack of a unified benchmark. To fill this gap, we introduce MetaBox, the first benchmark platform expressly tailored for developing and evaluating MetaBBO-RL methods. MetaBox offers a flexible algorithmic template that allows users to effortlessly implement their unique designs within the platform. Moreover, it provides a broad spectrum of over 300 problem instances, collected from synthetic to realistic scenarios, and an extensive library of 19 baseline methods, including both traditional black-box optimizers and recent MetaBBO-RL methods. Besides, MetaBox introduces three standardized performance metrics, enabling a more thorough assessment of the methods. In a bid to illustrate the utility of MetaBox for facilitating rigorous evaluation and in-depth analysis, we carry out a wide-ranging benchmarking study on existing MetaBBO-RL methods. Our MetaBox is open-source and accessible at: https://github.com/GMC-DRL/MetaBox.

Key facts. Cited by 35 papers in the map (data through 7 Oct 2026). Builds on 16 of its 57 references that are in the map. First posted on arXiv 12 Oct 2023.

Builds on

16 of 57 references.

References · 16

  1. 2017Proximal Policy Optimization Algorithmscited by 14,441
  2. 2015Deep Reinforcement Learning with Double Q-learningcited by 1,704
  3. 2017Evolution Strategies as a Scalable Alternative to Reinforcement Learningcited by 555
  4. 2015Scalable Bayesian Optimization Using Deep Neural Networkscited by 284
  5. 2021Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020cited by 146
  6. 2016COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Settingcited by 135
  7. 2022Discovering Evolution Strategies via Meta-Black-Box Optimizationcited by 44
  8. 2019Deep Reinforcement Learning Based Parameter Control in Differential Evolutioncited by 37
  9. 2023Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimizationcited by 33
  10. 2018IOHprofiler: A Benchmarking and Profiling Tool for Iterative Optimization Heuristicscited by 28
  11. 2020Olympus: a benchmarking framework for noisy optimization and experiment planningcited by 28
  12. 2021Learning adaptive differential evolution algorithm from optimization experiences by policy gradientcited by 24
4 more
  1. 2021IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristicscited by 24
  2. 2019Meta-Learning for Black-box Optimizationcited by 18
  3. 2021Meta Learning Black-Box Population-Based Optimizerscited by 13
  4. 2019Bayesian active learning for optimization and uncertainty quantification in protein dockingcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 12; 2025: 16; 2026: 7.

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  1. 2024ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolutioncited by 266
  2. 2024LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generationcited by 45
  3. 2024Cross-Problem Learning for Solving Vehicle Routing Problemscited by 24
  4. 2024Toward Automated Algorithm Design: A Survey and Practical Guide to Meta-Black-Box-Optimizationcited by 23
  5. 2024Auto-configuring Exploration-Exploitation Tradeoff in Evolutionary Computation via Deep Reinforcement Learningcited by 17
  6. 2024ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement Learningcited by 15
  7. 2024Pretrained Optimization Model for Zero-Shot Black Box Optimizationcited by 13
  8. 2025Reinforcement Learning-based Self-adaptive Differential Evolution through Automated Landscape Feature Learningcited by 12
  9. 2024DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Designcited by 11
  10. 2024Neural Exploratory Landscape Analysis for Meta-Black-Box-Optimizationcited by 10
  11. 2025MetaBox-v2: A Unified Benchmark Platform for Meta-Black-Box Optimizationcited by 9
  12. 2024RLEMMO: Evolutionary Multimodal Optimization Assisted By Deep Reinforcement Learningcited by 7
23 more
  1. 2024PARCO: Parallel AutoRegressive Models for Multi-Agent Combinatorial Optimizationcited by 7
  2. 2024AI Benchmarks and Datasets for LLM Evaluationcited by 7
  3. 2025Surrogate Learning in Meta-Black-Box Optimization: A Preliminary Studycited by 7
  4. 2025Instance Generation for Meta-Black-Box Optimization through Latent Space Reverse Engineeringcited by 6
  5. 2025Advancing CMA-ES with Learning-Based Cooperative Coevolution for Scalable Optimizationcited by 4
  6. 2025RedAHD: Reduction-Based End-to-End Automatic Heuristic Design with Large Language Modelscited by 4
  7. 2025AutoEP: LLMs-Driven Automation of Hyperparameter Evolution for Metaheuristic Algorithmscited by 4
  8. 2025Experience-Guided Reflective Co-Evolution of Prompts and Heuristics for Automatic Algorithm Designcited by 4
  9. 2025BBOPlace-Bench: Benchmarking Black-Box Optimization for Chip Placementcited by 4
  10. 2025LiBOG: Lifelong Learning for Black-Box Optimizer Generationcited by 3
  11. 2025A Novel Two-Phase Cooperative Co-evolution Framework for Large-Scale Global Optimization with Complex Overlappingcited by 2
  12. 2026Task-free Adaptive Meta Black-box Optimizationcited by 2
  13. 2025PlatMetaX: An Integrated MATLAB platform for Meta-Black-Box Optimizationcited by 1
  14. 2025Learning Where, What and How to Transfer: A Multi-Role Reinforcement Learning Approach for Evolutionary Multitaskingcited by 1
  15. 2026Detect and Act: Automated Dynamic Optimizer through Meta-Black-Box Optimizationcited by 1
  16. 2026Meta-Black-Box Optimization with Ensemble Surrogate Modeling for Robustness-Accuracy Trade-off within SAEAcited by 1
  17. 2025Reinforcement learning Based Automated Design of Differential Evolution Algorithm for Black-box Optimizationcited by 0
  18. 2025Island-Based Evolutionary Computation with Diverse Surrogates and Adaptive Knowledge Transfer for High-Dimensional Data-Driven Optimizationcited by 0
  19. 2025Your Offline Policy is Not Trustworthy: Bilevel Reinforcement Learning for Sequential Portfolio Optimizationcited by 0
  20. 2026Surrogate Ensemble in Expensive Multi-Objective Optimization via Deep Q-Learningcited by 0
  21. 2026NeurGO: Learning to Generate Elite Candidates for Meta-Black-Box Expensive Optimizationcited by 0
  22. 2026Beyond Scripted Search: Sample-Efficient Reward Discovery via Agentic Black-box Optimizationcited by 0
  23. 2026Hyper Algorithm Design Agent: Evolving Learnable Optimizer from Zerocited by 0