Abstract
Algorithmic specified complexity (ASC) measures the degree to which an object is meaningful. Neither fundamental Shannon nor Kolmogorov information models are equipped to do so. ASC uses performance context in an information theoretic framework to measure the degree of specified complexity in bits. To illustrate, we apply ASC to Conway’s Game of Life to differentiate patterns designed by programmers from those originating by chance. A variety of machines created by Game of Life hobbyists, as expected, exhibit high ASC thereby corroborating ASC’s efficacy.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Systems, Man, and Cybernetics: Systems
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.
