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

Two-level evolution of foraging agent communities.

Manuel Alfonseca1, Juan de Lara

  • 1Department Ingenieri;a Informática, Universidad Autónoma de Madrid, Ctra. De Colmenar, km. 15, Spain.

Bio Systems
|September 3, 2002
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

Evolving an ecology of mathematical expressions with grammatical evolution.

Bio Systems·2013
Same author

A threaded Java concurrent implementation of the Monte-Carlo Metropolis Ising model.

International Work-Conference on the Interplay between Natural and Artificial Computation·2011
Same journal

The bridges evolution built: In search of mechanisms that couple scales of perception and action.

Bio Systems·2026
Same journal

Spatiotemporal bursting in simulated cultures of cortical neurons.

Bio Systems·2026
Same journal

A brief discussion on recent models shedding light on how life emerged.

Bio Systems·2026
Same journal

Memory-based strategy reputation and adaptive learning in spatial evolutionary games: A robust agent-based model for cooperation dynamics.

Bio Systems·2026
Same journal

Coherent Photonic Biofields: Revisiting Fritz-Albert Popp's Hypothesis.

Bio Systems·2026
Same journal

Ruliological Resilience: Pattern Restoration and Robustness in Wolfram Patterns. A Basis for Regeneration, Not Just in Cone Shells?

Bio Systems·2026
See all related articles

Artificial foraging agents simulate ant-like behaviors to find food and communicate locations. Genetic recombination and nest dynamics lead to emergent cooperation and competition.

Area of Science:

  • Artificial intelligence
  • Computational biology
  • Agent-based modeling

Background:

  • Simulating complex behaviors in artificial agents is crucial for understanding emergent phenomena.
  • Ant colonies provide a natural model for studying foraging, communication, and social dynamics.

Purpose of the Study:

  • To simulate artificial foraging agent communities to investigate emergent behaviors.
  • To explore the impact of genetic traits and nest dynamics on agent interactions.

Main Methods:

  • Agent-based simulation of foraging agents with genetic attributes.
  • Modeling of food discovery, resource transport, and inter-agent communication.
  • Incorporation of genetic recombination, sexual reproduction, and nest splitting mechanisms.

Related Experiment Videos

Main Results:

  • Emergent cooperation and competition observed within and between agent nests.
  • Simulation of phenomena like rumor propagation influenced by agent communication.
  • Demonstration of how genetic characteristics influence agent behavior and community dynamics.

Conclusions:

  • Agent-based simulations can effectively model complex social behaviors and emergent phenomena.
  • Genetic and environmental factors significantly shape the evolution of cooperation and competition.
  • The study provides insights into the principles governing collective intelligence and social organization.