Synthesized answer
Dynamical complexity addresses the limitations of existing complexity definitions developed for "information-theoretic objects" by providing a physical interpretation of mathematical complexity theory [1, 3]. While concepts like "effective complexity" work well for signals, they are not directly applicable to physical and social systems like the global climate [1, 3]. Dynamical complexity aims to bridge this gap, transforming a discussion of complexity that functions for messages into one that works for climate systems [3].
The passages suggest that dynamical complexity is intended to provide a framework for understanding complex physical systems, allowing for a clearer distinction between intuitively simple and complex systems, such as a free photon in a vacuum versus the global climate [4]. It is proposed as a means to analyze the structure of science generally and can be used to understand how climate science constructs and trusts its models [1]. The passages state that the global climate is a paradigmatic dynamically complex system, and recognizing this is crucial for addressing climate change [4, 5].
Synthesized from the book passages below. Chat with the book on Feynman for follow-up.
From the book
formation-theoretic objects (signals, for instance) rather than the physical and social systems studied by scientists. Dynamical complexity, a concept articulated in detail in the first third of the dissertation, is designed to bridge the gap between the mathematics of contemporary complexity theory (in particular the formalism of “effective complexity” developed by Gell-Mann and Lloyd [2003]) and a more general account of the structure of science generally. Dynamical complexity provides a physical interpretation of the formal tools of mathematical complexity theory, and thus can be used as…
s dynamical complexity is the sum of the effective complexity values for all relevant ways of representing the system. See Section 2.2.2 for more on this. In this chapter, I would like to narrow our focus and apply some of the concepts we’ve developed over the last hundred (or so) pages to more practical concerns. In Chapter Zero , I argued that the issue of global climate change is perhaps the most pressing scientific problem of our time, and suggested that the paucity of philosophical engagement with this problem is a travesty in need of serious attention. Chapter One consisted of a…
up that project, and present a novel account of what it means for a physical system to be complex in the relevant sense. This concept, which I will call dynamical complexity , is presented as a physical interpretation of some very recent mathematical advancements in the field of information theory. The central problem that shall occupy us in the next chapter, then, is how to transform a discussion of complexity that seems to work very well for things like messages into an account that works well for things like climate systems. My hope is that dynamical complexity offers this bridge. Once…
ystems that seem intuitively "simple" (e.g. a free photon in a vacuum) and systems that seem intuitively "complex" (e.g. the global climate) more clearly, and to begin to get a grasp on important differences between the methods of sciences that study systems with high dynamical complexity and those of sciences that study systems with low dynamical complexity. I then argue that, based on this definition, climate science is a paradigmatic complex-systems science, and that recognition of this fact is essential if we're to bring all our resources to bear on solving the problems posed by climate…
with a system of high dynamical complexity, and think about and how have those challenges been met in different fields. We’ll examine why it is that scientists care about dynamical complexity, and what can be learned by assessing the dynamical complexity of a given system. In Chapter Five , I’ll synthesize the two threads that have, up to that point, been pursued more-or-less in parallel and argue the global climate is a paradigmatic dynamically complex system. We’ll examine how that fact has shaped the methodology of climate science, as well as how it has given rise to a number of unique…
More questions about this book
- How do foundational questions like "What makes a system complex?" directly influence and inform the approach taken to methodological questions concerning the construction, trust, and improvement of climate models?
- If "dynamical complexity" provides a "physical interpretation of the formal tools of mathematical complexity theory," what specific insights might this offer for understanding fundamental concepts like "theories, explanation, and lawhood" within the philosophy of science?
- Considering climatology as a "paradigmatic complex systems science," how does the "interaction of many different components operating at many different temporal and spatial scales" necessitate a multidisciplinary approach, and what unique challenges does this present for scientific understanding?
- Lawhead identifies "How do we know that we can trust science?" as a surprisingly difficult foundational question. How might the proposed framework of "dynamical complexity" contribute to answering this question, particularly in the context of highly complex systems like the global climate?