ProQuest Dissertations And Theses; Thesis (Ph.D.)–Arizona State University, 2017.; Publication Number: AAT 10681325; ISBN: 9780355511048; Source: Dissertation Abstracts International, Volume: 79-04(E), Section: B.; 236 p.
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What makes living systems different than non-living ones? Unfortunately this
question is impossible to answer, at least currently. Instead, we must face computationally tangible questions based on our current understanding of physics, computation,
information, and biology. Yet we have few insights into how living systems might
quantifiably differ from their non-living counterparts, as in a mathematical foundation
to explain away our observations of biological evolution, emergence, innovation, and
organization. The development of a theory of living systems, if at all possible, demands
a mathematical understanding of how data generated by complex biological systems
changes over time. In addition, this theory ought to be broad enough as to not be
constrained to an Earth-based biochemistry. In this dissertation, the philosophy of
studying living systems from the perspective of traditional physics is first explored as
a motivating discussion for subsequent research. Traditionally, we have often thought
of the physical world from a bottom-up approach: things happening on a smaller scale
aggregate into things happening on a larger scale. In addition, the laws of physics
are generally considered static over time. Research suggests that biological evolution
may follow dynamic laws that (at least in part) change as a function of the state of
the system. Of the three featured research projects, cellular automata (CA) are used
as a model to study certain aspects of living systems in two of them. These aspects
include self-reference, open-ended evolution, local physical universality, subjectivity,
and information processing. Open-ended evolution and local physical universality are
attributed to the vast amount of innovation observed throughout biological evolution.
Biological systems may distinguish themselves in terms of information processing and
storage, not outside the theory of computation. The final research project concretely
explores real-world phenomenon by means of mapping dominance hierarchies in the
evolution of video game strategies. Though the main question of how life differs
from non-life remains unanswered, the mechanisms behind open-ended evolution and
physical universality are revealed.