A (Growing) Paper List of Evolutionary Computation (EC) on Top-Tier Publications (e.g., Nature, Science, etc.)
This is a growing paper list for evolutionary computation (EC). Currently we are actively updating it (at least from 2021 to 2024). Owing to the abundance of the related literature, however, we believe that many interesting works are still missed here. If you find them missed, welcome to contact with us via Issues or Pull requests to add. Recently, we notice that some other research group(s) also starts to adopt a similar way to collect EC literatures, which is a good news (following us).
NOTE: Although our initial goal was to cover only parallel and distributed EC, now our focus is switched to Evolutionary Computation (EC) researches and applications for (>30) chosen journals and conferences (such as Nature, Science, PNAS, PRL, JACS, PIEEE, Nature Materials, Nature Chemistry, Nature Genetics, Nature Neuroscience, Nature Geoscience, Nature Photonics, Nature Nanotechnology, Nature Sustainability, Nature Human Behaviour, Nature Ecology & Evolution, Science Robotics etc.) besides EC-specific publications (e.g., ECJ/IEEE-TEVC/ACM-TELO/ACM-FOGA/PPSN/ACM-GECCO/IEEE-CEC/...). For EC-focused publications, currently still only Parallel/Distributed EC are covered. The total number of journals and conferences chosen in this repository are still considered to increase in the future.
WARNING: In this paper repository, we do NOT judge the scientific(theoretical)/engineering(practical) value of each paper, since such a value judgement is often a non-trival task. Instead, we ONLY provide a widely-accessible platform to collect papers regarding EC on some (rather all) top-tier and also related EC-focused journals as much as possible. Since only PDEC are covered for EC-focused publications, this paper collection may be somewhat biased, which should be noticed.
"Frequently nonadditive interaction (i.e., "epistasis" or "nonlinearity") makes it impossible to determine the performance of a structure from a study of its isolated parts. While these difficulties pose a real problem for the analyst, we know that they are routinely handled by biological adaptive processes, qua processes."---[John H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, 1992]
Here, we consider a family of evolutionary algorithms (and also several closely-related techniques, e.g. random search and simulated annealing). Since initially we focused primarily on their parallel/distributed versions and variants, we provide a reference list for their original / seminal / landmark / survey / review / opinion papers, in order to help better understand them (especially for newcomers). We strongly suggest to see e.g. 2015's Review paper in Nature or 1993's Review paper in Science.
- Four Conventional EAs
- Genetic Algorithms (GA)
- Evolution Strategies (ES) [ applications ]
- Covariance Matrix Adaptation ES (CMA-ES)
- Evolutionary Programming (EP)
- Genetic Programming (GP)
- Two Swarm Intelligence (SI) Siblings
- Two Representative Multi-Objective Optimization (MOO) Evolutionary Frameworks
- Several Relatively New Extensions/Improvements/Variants
- Co-Evolutionary Algorithms (CEA)
- Differential Evolution (DE)
- Memetic Algorithms (MA)
- Estimation of Distribution Algorithms (EDA)
- Natural Evolution Strategies (NES)
- Quality-Diversity (QD)
- Multidimensional Archive of Phenotypic Elites (MAP-Elites)
- NeuroEvolution (aka Evolving Neural Networks)
- Evolutionary/Swarm Robotics (ER/SR)
- Artificial Life (AL)
- Open-Ended Evolution
- Common Individual-based Counterparts/Baselines/Competitors (especially for their stochastic versions)
- Random Search (RS)
- Local Search (LS) / Hill Climbers (HC)
- Simulated Annealing (SA)
- Tabu Search (TS)
"Responsible for adaptation, optimization, and innovation in the living world, evolution executes a simple algorithm of diversifcation and natural selection, an algorithm that works at all levels of complexity from single protein molecules to whole ecosystems."---Nobel Lecture, by Frances H. Arnold, California Institute of Technology
This ongoing paper list for EC (PDEC) is now supported by Shenzhen Fundamental Research Program under Grant No. JCYJ20200109141235597 (￥2,000,000, granted to Prof. Shi from CSE, SUSTech @ Shenzhen, China), and is actively maintained/updated (from 2021 to 2023) by his group members (e.g., Qiqi Duan). We also acknowledge the early contribution from Vincent A. Cicirello.