All Types of Systems are Generally Comparable fact

All Systems are Generally Analogous

General Systems Theory: Finding Common Features Between Different Types of Physical and Conceptual Systems

General systems theory shows us there are commonalities between different types of physical and conceptual systems which we can study to better understand complex systems.

We can look at systems either by looking at their parts (analysis), or by looking at their parts in relation to each other (synthesis), or by looking at how systems interact with other systems (also synthesis). By looking at systems from different angles and studying comparative features and similarities, we give ourselves a different reference frame potentially increasing our odds of making new discoveries.

For instance we can compare an quantum particles, binary code, and integers with some relative success, perhaps learning something about how duality works in the process. Or perhaps we compare the way a flock of birds fly to a squadron of jets to better understanding how to design the planes for dynamic soaring. The possibilities are near endless.

Complex systems can be difficult to understand, but this is why comparing systems and finding similar features has merit. The science behind systems theory, and specifically general systems theory (which looks at commonalities between systems), can help paint a clearer picture.

Below we explore how general systems theory can be used to better understand complex systems.

Introduction to Complex Systems: Patterns in Nature. The easiest way to understand systems is by looking at the very familiar, thus this video is a good introduction.

TIP: If you find complex systems interesting I strongly suggest checking out Conway’s the Game of Life, elementary particles and fundamental forces, and the evolution of complex cells.

What are Systems, Systems Theory, and Complexity Science?

Systems are models for understanding concepts and the physical universe. When we analyze systems it’s called systems theory, when we study complex systems it is complexity theory. Specifically:

  • The study of how systems work is called systems theory.
  • The study of how complex systems work is called complexity theory.
  • The study of the commonalities between systems is called general systems theory.
  • The study of all systems, including complex systems, is called complexity science.

All of this is simply the study of systems through models and rule-sets (AKA theories).

Learn more about systems in general here.

Analysis and Synthesis

To look at systems we need to use analysis (deductive reasoning) and synthesis (inductive reasoning):

  • Analysis looking at the elements by breaking them down to their core.
  • Synthesis studying the relationship between elements and systems

In other words, we don’t want to just take a traditional western approach where we dissect the frog to understand the frog, we want to see how the parts of a single frog move together, and how frogs act alone, in groups, and in pairs.

video explaining Systems Theory, specifically it explains analysis and synthesis.

General Systems Theory

General Systems Theory aims to trace a line between all systems. Sort of like unifying the forces in particle physics, I don’t think anyone has presented a solidly perfect theory. But below is a breakdown of Ludwig von Bertalanffy’s general systems theory which shows four interconnected domains of general systems theory that work hand-in-hand.

Philosophy and Theory act as Knowledge, and Method and Application act as action, and then these can be applied to any of the domains (like specifically Philosophy, Science, and Technology) as knowledgeable action.

Domain Description
Philosophy the ontology, epistemology, and axiology of systems;
Theory a set of interrelated concepts and principles applying to all systems
Methodology the set of models, strategies, methods, and tools that instrumentalize systems theory and philosophy
Application the application and interaction of the domains

Complex Science and General Systems Theory: Using Analysis, Synthesis, to Create Rule-sets

Understanding complex systems and coming up with rule-sets can be next to impossible with just one sort of reasoning, or by taking any narrow view. As you can imagine, getting a theory of everything and understanding the mechanics of conceptual and physical systems requires thinking outside “the bounds”.

To get ultra general rule sets that apply to systems broadly we have to look at systems from every angle we can.

Instead of relying on one type of analysis, we can use a mix of analysis and synthesis to study complex systems, their interrelations, and their relationships to other systems. We can even apply concepts and analogies from other arts and sciences to help devise core rule sets that are “generally analogous” to all systems.

In theory, everything that exists in the physical universe, and thus, generally shares a foundation properties that we can model. We can compare systems and find commonalities between them. This can result in rule-sets that can be applied broadly between all systems, or just between types of systems.

Rule-sets like that can help us shed light on mysteries we couldn’t unravel as easily otherwise. This line of thinking is general systems theory, which applies to complexity theory and complexity science.

Below we explore different types of physical and conceptual systems and show how they are analogous.

Complex Adaptive Systems: 1 Complexity Theory.

FACT: Complexity itself is one of the core properties shared by most systems. Even a simple rule-set can produce wildly complex results (example: Conway’s The Game of Life).

Systems Theory - Complexity Map

This chart traces a line from the roots of systems theory, to complexity science, to today..

The Foundation of all Systems is Generally Analogous

All systems are rooted in our physical universe (as that is where we live), and thus it stands to reason all systems generally share a foundation. To find that foundation we can look to fundamentals like binary and quantum computing, elementary particles, randomization, basic electrical and thermodynamic systems, mass-energy equivalence, neural networks, complex cell evolution, basic game theory, societies that formed around the fertile crescent, etc.

Different Systems Share Core Properties

Core properties of systems (and ways we perceive and model systems) like: entropy, frames of reference, relativity, order of operations, conservation of energy (and other conservation laws), probability and odds, a “center”, duality, attraction and repulsion (charge), symmetry and asymmetry (balance), infinity, efficiency, motion, limits, coordinates, square roots, and more all tend to be common to most of the physical and non-physical systems we model.

Whether it’s a physical system of properties or a conceptual system (science or imagination based), all systems can be explained in the language of rule-sets, math, and models. With a bit of critical thinking we can trace lines with broad strokes to show how different systems are roughly analogous to each other. With a bit more critical thinking we could likely devise models, rule-sets, and equations that connect models to each other helping us to better understand each system individually and all systems independently.

In short, whether it’s a computer system, a gambling system, an atom, the universe, a human cell, a human, the standard model, video game tactics, a playbook for a sports team, a weight loss routine, or “whatever” we see the same core properties pop-up over and over and the same techniques can be used to model these systems.

This video looks at sets and systems in detail. I highly recommend the Complexity Academy series, if you couldn’t tell.

FACT: Systems theory is the study of systems in general. The goal of studying systems is discovering patterns and principles that can be discerned from, and applied to, all types of systems in all fields of research. See a list of types of systems in systems theory here.


Systems theory is based on the idea that systems are generally analogous. There is lots of examples to show this as true, but ultimately it’s in the territory of theory.


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Author: Thomas DeMichele

Thomas DeMichele is the content creator behind,,, and other and Massive Dog properties. He also contributes to MakerDAO and other cryptocurrency-based projects. Tom's focus in all...

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