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

Flexible couplings: diffusing neuromodulators and adaptive robotics.

Andy Philippides1, Phil Husbands, Tom Smith

  • 1Centre for Computational Neuroscience and Robotics (CCNR), Department of Informatics, University of Sussex, Brighton, UK. andrewop@sussex.ac.uk

Artificial Life
|April 7, 2005
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

Assessing cognition in autistic youth with and without attention-deficit/hyperactivity disorder using the NIH Toolbox Cognition Battery: An Environmental influences on Child Health Outcomes-Wide Cohort Study.

JCPP advances·2026
Same author

Subcellular chemical mapping using correlated cryogenic electron and mass spectrometry imaging.

Nature methods·2026
Same author

Pharmacokinetics, safety and preliminary efficacy study of montelukast in critically ill infants with developing bronchopulmonary dysplasia (PRISM).

Contemporary clinical trials communications·2026
Same author

Functional characterisation of tumour suppressor PDCD4 reveals previously undisclosed role in the control of cell adhesion.

Nucleic acids research·2026
Same author

Inhibiting translation elongation by reducing eIF5A activity induces feedback inhibition of initiation, limiting tumour cell proliferation.

Nature communications·2025
Same author

Industrial and agricultural chemicals exhibit antimicrobial activity against human gut bacteria in vitro.

Nature microbiology·2025
Same journal

If Turing Played Piano With an Artificial Partner.

Artificial life·2026
Same journal

Discovering Partial Differential Equations With Neural Cellular Automata.

Artificial life·2026
Same journal

System 0/1/2/3: Quad-Process Theory for Multitimescale Embodied Collective Cognitive Systems.

Artificial life·2025
Same journal

Untapped Potential in Self-Optimization of Hopfield Networks: The Creativity of Unsupervised Learning.

Artificial life·2025
Same journal

Vants and Turmites.

Artificial life·2025
Same journal

Automating the Search for Artificial Life With Foundation Models.

Artificial life·2025
See all related articles

New GasNet models inspired by gaseous neurotransmitters significantly improve artificial neural network evolvability in robotics. These advancements enhance the speed and consistency of developing effective sensorimotor behaviors.

Area of Science:

  • Neuroscience
  • Artificial Intelligence
  • Robotics

Background:

  • Biological nervous systems utilize freely diffusing gaseous neurotransmitters like nitric oxide (NO).
  • Artificial neural networks (ANNs) inspired by gaseous signaling, termed GasNets, exhibit enhanced evolvability in evolutionary robotics.
  • Evolvability is defined as the consistent speed to achieve effective sensorimotor behavior-generating systems.

Purpose of the Study:

  • To introduce two novel GasNet models inspired by neuronal gaseous signaling properties.
  • To investigate if these new models further improve the evolvability of artificial nervous systems.
  • To analyze the underlying mechanisms contributing to enhanced evolvability.

Main Methods:

  • Development of two new GasNet models: the plexus model and the receptor model.

Related Experiment Videos

  • Inspiration drawn from the NO-producing cortical plexus and neurotransmitter receptor actions.
  • Evaluation of model performance in an evolutionary robotics setting.

    • Main Results:

    • Both the plexus and receptor GasNet models demonstrated significant improvements in evolvability.
    • The enhanced evolvability is linked to a flexible, loose coupling between chemical and electrical signaling mechanisms.
    • Consistent and faster achievement of appropriate sensorimotor behaviors was observed.

    Conclusions:

    • Novel GasNet architectures inspired by biological gaseous neurotransmission enhance artificial nervous system evolvability.
    • The integration of chemical and electrical signaling pathways offers a promising direction for future AI development.
    • These findings suggest a pathway for creating more adaptable and efficient artificial intelligence systems.