Abstract
We present a method for predicting the large-scale evolution of a tag system from its production rules. A tag system's evolution is first divided into stages called `epochs' in which the tag system evolves monotonously. The distribution of symbols in the queue at the beginning of each epoch determines the tag system's large-scale properties, including growth rate and string densities, during that epoch. We derive the symbol distribution for the next epoch from the distribution for the current one, using this to make predictions over multiple successive epochs. Finally, we compare predictions that were obtained with this method to computer simulations and find that it retains great accuracy over several epochs.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.