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 Experiment Videos

Evolving mobile robots able to display collective behaviors.

Gianluca Baldassarre1, Stefano Nolfi, Domenico Parisi

  • 1Institute of Cognitive Sciences and Technologies, National Research Council (ISTC-CNR), 15 Viale Marx, 00137 Rome, Italy. baldassarre@ip.cnr.it

Artificial Life
|October 15, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Functional and clinical outcomes of propeller flaps in lower extremity reconstruction: A systematic review.

JPRAS open·2026
Same author

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

Scientific reports·2026
Same author

From Spontaneous Ignitions to Sensorimotor Cell Assemblies via Dopamine: A Spiking Neurocomputational Model of Infants' Hand Action Acquisition.

Brain sciences·2026
Same author

Modeling metacognition and executive functions in the metacognitive wisconsin card sorting test using the neuropsychological digital-twin method.

Scientific reports·2026
Same author

Skin Cancers in People Living with Human Immunodeficiency Virus (HIV) Infection.

Journal of clinical medicine·2025
Same author

Assessing executive functions and metacognition: translational potential of the Metacognitive Wisconsin Card Sorting Test for developmental neuropsychology.

Frontiers in behavioral neuroscience·2025

Simulated robots evolved to aggregate and move toward light targets. Evolved groups demonstrated collective behavior, acting as a unit with emergent specialization, showcasing evolutionary algorithms for swarm robotics.

Area of Science:

  • Robotics
  • Artificial Intelligence
  • Evolutionary Computation

Background:

  • Collective behavior in natural systems.
  • Challenges in programming swarm robotics.
  • Potential of evolutionary algorithms for emergent behaviors.

Purpose of the Study:

  • To evolve simulated robots for aggregation and coordinated movement.
  • To analyze emergent group structures and behaviors.
  • To demonstrate the efficacy of evolutionary techniques in synthesizing collective robot behavior.

Main Methods:

  • Evolutionary algorithms applied to simulated robots.
  • Development of quantitative indexes for formation analysis.
  • Observation of robot-environment and robot-robot interactions.

Related Experiment Videos

Main Results:

  • Evolved robots aggregated and moved cohesively towards a light target.
  • Quantitative analysis revealed robots acting as a single unit.
  • Identical controllers led to emergent situated specialization and functional roles within groups.

Conclusions:

  • Evolutionary computation is a powerful tool for synthesizing collective robot behavior.
  • Self-organization principles emerge from robot-environment interactions.
  • Evolved systems can display complex group dynamics and specialization.