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

From machine and tape to structure and function: formulation of a reflexively computing system.

Chris Salzberg1

  • 1Ikegami Lab, Department of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan. chris@sacral.c.u-tokyo.ac.jp

Artificial Life
|September 7, 2006
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

A graph-based reflexive artificial chemistry.

Bio Systems·2006
Same author

Visualizing evolutionary dynamics of self-replicators: a graph-based approach.

Artificial life·2006
Same author

Evolutionary dynamics of cellular automata-based self-replicators in hostile environments.

Bio Systems·2004
See all related articles

This study introduces a novel computational model where structure and function dynamically interact, enabling self-modification. This reflexive dynamic is key to understanding complex systems like biochemical processes.

Area of Science:

  • Theoretical computer science
  • Biophysics
  • Formal systems

Background:

  • Traditional models often impose rigid boundaries between structure and function.
  • Previous computational models lacked a dynamic, reflexive relationship between an object's form and its operations.

Purpose of the Study:

  • To explore the emergent relationship between structure and function in a novel computational framework.
  • To demonstrate computation universality and model self-computing systems.
  • To propose a new perspective on informational dynamics in biochemical systems.

Main Methods:

  • Utilizing labeled directed graph structures with a single, local read/write rule.
  • Mapping Turing machine components (tape squares, states) to graph nodes and links.

Related Experiment Videos

  • Developing a formulation that allows objects to act upon their own structure.

    • Main Results:

    • Established computation universality by representing arbitrary Turing machines.
    • Demonstrated unconventional "self-computing" structures and a kinematic machine system.
    • Showcased emergent boundaries between static and active objects through structure-function dynamics.

    Conclusions:

    • Reflexivity of the structure-function relationship is a critical, previously overlooked dynamic in biochemical systems.
    • The proposed formulation offers a flexible and powerful model for computation and construction.
    • This framework advances the understanding of self-organizing and self-computing systems.