ReviewNature2015
From evolutionary computation to the evolution of things.
Review in Nature, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
38 citing papers in PubMed.
- Evolvable AI: Threats of a new major transition in evolution.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Machine learning for estimation and control of quantum systems.National science review · 2025Review
- When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challenges.Research (Washington, D.C.) · 2025Review
- Bioengineering hybrid artificial life.Frontiers in bioinformatics · 2025Review
- Freeform generative design of complex functional structures.Scientific reports · 2024Article
- Using the Grey Wolf Aquila Synergistic Algorithm for Design Problems in Structural Engineering.Biomimetics (Basel, Switzerland) · 2024Article
- Exploring the costs of phenotypic plasticity for evolvable digital organisms.Scientific reports · 2024Article
- Nature-Inspired Intelligent Computing: A Comprehensive Survey.Research (Washington, D.C.) · 2024Review
- Evolutionary robotics as a modelling tool in evolutionary biology.Frontiers in robotics and AI · 2024Article
- Article
- Maximum Lyapunov exponent-based multiple chaotic slime mold algorithm for real-world optimization.Scientific reports · 2023Article
- A game-theoretic model for the classification of selected oil companies' price changes.PeerJ. Computer science · 2023Article
- Controlling gene expression with deep generative design of regulatory DNA.Nature communications · 2022Article
- Robots as models of evolving systems.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Multi-Objective Drug Design Based on Graph-Fragment Molecular Representation and Deep Evolutionary Learning.Frontiers in pharmacology · 2022Article
- From the lab to the field with Evolutionary Field Robotics.Frontiers in robotics and AI · 2022Article
- Editorial: Evolving Robotic Morphologies.Frontiers in robotics and AI · 2022Article
- A complex systems perspective of news recommender systems: Guiding emergent outcomes with feedback models.PloS one · 2021Article
- Real-World Robot Evolution: Why Would it (not) Work?Frontiers in robotics and AI · 2021Review
- Robot Evolution: Ethical Concerns.Frontiers in robotics and AI · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Evolution has provided a source of inspiration for algorithm designers since the birth of computers. The resulting field, evolutionary computation, has been successful in solving engineering tasks ranging in outlook from the molecular to the astronomical. Today, the field is entering a new phase as evolutionary algorithms that take place in hardware are developed, opening up new avenues towards autonomous machines that can adapt to their environment. We discuss how evolutionary computation compares with natural evolution and what its benefits are relative to other computing approaches, and we introduce the emerging area of artificial evolution in physical systems.
Indexed as
Identifiers
26017447What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.