Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Microbial Morphologies01:29

Microbial Morphologies

53
Bacterial and archaeal cells exhibit remarkable diversity in shape and structure, critical in their adaptability and functionality. Among bacteria, the most commonly observed shapes include cocci and bacilli. Cocci are spherical and may exist singly or in groupings such as pairs (diplococci), chains (streptococci), clusters (staphylococci), or tetrads. Bacilli, in contrast, are rod-shaped and can also occur as single cells, in pairs, or chains, depending on their environmental and genetic...
53
Limits to Natural Selection01:38

Limits to Natural Selection

31.4K
Organisms that are well-adapted to their environment are more likely to survive and reproduce. However, natural selection does not lead to perfectly adapted organisms. Several factors constrain natural selection.
31.4K
Genetic Variation01:25

Genetic Variation

329
Genetic variation is the diversity in DNA sequences found among individuals of the same species. This diversity is crucial for a species' survival because it helps organisms adapt to environmental changes. Genetic variation begins with fertilization, where an egg and sperm cell merge. Each of these cells carries 23 chromosomes, up to 46 in the fertilized egg. Chromosomes are long DNA strands that contain genes, the basic units of heredity.
Genes exist in different versions called alleles,...
329
What is Variation?01:14

What is Variation?

12.1K
Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of any data set is its variation or spread. In some data sets, the data values are concentrated closely near the mean; in others, the data values are more widely spread out from the mean.
The range, standard deviation, standard error, and variance are the different measures of variation.
Range: The range is the difference between its maximum and...
12.1K
Mutation, Gene Flow, and Genetic Drift01:09

Mutation, Gene Flow, and Genetic Drift

58.7K
In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
58.7K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.8K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
5.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Sensory-motor control with large language models via iterative policy refinement.

Scientific reports·2026
Same author

Global progress in competitive co-evolution: a systematic comparison of alternative methods.

Frontiers in robotics and AI·2025
Same author

Interaction Rules Supporting Effective Flocking Behavior.

Artificial life·2024
Same author

Progress and challenges in adaptive robotics.

Frontiers in robotics and AI·2022
Same author

Phenotypic complexity and evolvability in evolving robots.

Frontiers in robotics and AI·2022
Same author

Automated curriculum learning for embodied agents a neuroevolutionary approach.

Scientific reports·2021

Related Experiment Video

Updated: Jul 25, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.7K

The Role of Morphological Variation in Evolutionary Robotics: Maximizing Performance and Robustness.

Jonata Tyska Carvalho1, Stefano Nolfi2

  • 1Informatics and Statistics Department, Federal University of Santa Catarina (UFSC), Florianópolis, Brazil Institute of Cognitive Sciences and Technologies (ISTC), National Research Council (CNR), Rome, Italy jonata.tyska@ufsc.br.

Evolutionary Computation
|June 30, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a method to analyze how robot controller evolution is affected by morphological variations. Results show evolutionary algorithms can tolerate significant variations, improving agent robustness and performance in diverse conditions.

Keywords:
Evolutionary roboticsevolution strategiesmorphological variation

More Related Videos

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.4K
Designing and Implementing Nervous System Simulations on LEGO Robots
10:34

Designing and Implementing Nervous System Simulations on LEGO Robots

Published on: May 25, 2013

15.1K

Related Experiment Videos

Last Updated: Jul 25, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

11.7K
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.4K
Designing and Implementing Nervous System Simulations on LEGO Robots
10:34

Designing and Implementing Nervous System Simulations on LEGO Robots

Published on: May 25, 2013

15.1K

Area of Science:

  • Robotics
  • Evolutionary Computation
  • Artificial Intelligence

Background:

  • Evolving robot controllers requires exposure to variable conditions for robustness and to bridge the reality gap.
  • Current methods lack analysis of how morphological variations impact evolutionary processes and suitable variation range selection.

Purpose of the Study:

  • To introduce a method for measuring the impact of morphological variations on robot controller evolution.
  • To analyze the relationship between variation amplitude, modality, and the performance/robustness of evolving agents.

Main Methods:

  • Developed a method to quantify the effects of morphological variations (initial state, sensor noise) on evolutionary algorithms.
  • Analyzed the performance and robustness of evolving agents under varying morphological conditions.

Main Results:

  • Evolutionary algorithms demonstrate tolerance to high-impact morphological variations.
  • Variations in agent actions are better tolerated than variations in initial states or environment.
  • Multiple fitness evaluations do not consistently improve accuracy.

Conclusions:

  • Morphological variations enhance the robustness and performance of evolved robot controllers.
  • The developed method aids in understanding and selecting appropriate variation ranges for evolutionary robotics.