Ladderpath Approach: How Tinkering and Reuse Increase Complexity and Information

Area of Science:

• Information theory
• Complexity science
• Evolutionary biology
• Exobiology
• Molecular biology

Background:

• Information and complexity are key in fields like molecular biology and evolutionary theory.
• Existing complexity measures are often computationally intensive, statistically based, or limited to string data.

Purpose of the Study:

• To propose a novel framework, the ladderpath, for quantifying information and complexity.
• To develop new complexity measures, the ladderpath-index and order-index, based on hierarchical decomposition.
• To demonstrate the broad applicability of the ladderpath approach across different systems.

Main Methods:

• Developing the ladderpath concept based on assembly theory.
• Defining the ladderpath-index and order-index as measures of complexity.
• Applying the ladderpath approach to analyze both strings and spatial patterns.

Main Results:

• The ladderpath framework provides a hierarchical decomposition of objects using repetitive elements.
• The ladderpath-index and order-index offer new axes for characterizing system complexity.
• The approach is applicable to strings and spatial patterns, suggesting universal relevance for evolving systems.

Conclusions:

• The ladderpath approach offers an alternative method for characterizing information within objects.
• This framework can enhance our understanding of evolving systems, particularly concerning the origin of life.
• Ladderpaths may have applications in analyzing human language and other complex systems.