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https://ceur-ws.org/Vol-3905/abstract3.pdf
A preliminary vocabulary of complexity
Evellin Cardoso1
1
Federal University of Goias, Goias, Brazil
Abstract
In 20th century, advances in physics (relativity, quantum mechanics, chaos and complex systems) led to the
development of the "paradigm of complexity". In this paradigm, scientists realized that the study of modern
phenomena could not be classified in any single discipline, thus requiring an interdisciplinary approach. However,
although complexity is one of the most promising areas in contemporary science, it is still a fragmented body of
knowledge, being composed of a plethora of methods, concepts and principles from a multitude of disciplines. To
tackle this conceptual gap, this work proposes a preliminary vocabulary of complexity.
Keyworks
complexity, complexity science, complex systems, vocabulary
1. Introduction
In 20th century, advances in physics (relativity, quantum mechanics, chaos and complex systems) led
to the development of the "paradigm of complexity" [1, p. 20]. In this paradigm, scientists realized
that the study of modern phenomena could not be classified in any single discipline, thus requiring an
interdisciplinary approach [1, 2]. However, although complexity is one of the most promising areas
in contemporary science, it is still a fragmented body of knowledge, being composed of a plethora of
methods, concepts and principles from a multitude of disciplines [1]. To tackle this conceptual gap, this
work proposes a preliminary vocabulary of complexity.
2. Research Method
Given its interdisciplinary nature, I chose four books from different disciplines as the starting points to
gather this vocabulary. The first book [1] is a guided tour in the area of complexity, covering the full
history of the topic. The second one [3] describes how philosophy addresses the topic of complexity, by
elaborating hypothesis about the subject, while the third [4] and fourth ones [2] are scientific books,
respectively from mathematics/simulation and physics.
3. Findings
Advances in complexity science are still cutting-edge research in many fields, and therefore, there is no
general consensus about the necessary and sufficient properties of complex systems. Below, I include
only the consensual terms:
Definition 1 (Sciences of Complexity). The Sciences of Complexity consists of an interdisciplinary
field of study whose goal is to understand how simple, independent entities without a central controller
dynamically interact to generate a coherent whole that strives to achieve collective goals, generate
patterns, exchange information, adapt and learn.
Proceedings of the 17th Seminar on Ontology Research in Brazil (ONTOBRAS 2024) and 8th Doctoral and Masters Consortium on
Ontologies (WTDO 2024), Vitória, Brazil, October 07-10, 2024.
*
Corresponding author.
$ evellin@ufg.br,evellinc@gmail.com (E. Cardoso)
0000-0001-6242-662X (E. Cardoso)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
ceur-ws.org
Workshop ISSN 1613-0073
Proceedings
At the heart of the sciences of complexity, there is the concept of complex systems, together with a
number of properties:
Definition 2 (Complex Systems). A complex system is a tuple 𝐶𝑠 =< 𝐸, 𝐼 >, where 𝐶𝑠 , E, I are,
respectively, a complex system, a set of elements within 𝐶𝑠 and a set of interactions on E.
• Elements. A complex system is composed of many elements, being them the prerequisite
for interactions to occur. These elements depend on the studied field (e.g., atoms in quantum
systems, cells in biology, ants and bees in biology, people and companies in economics, etc.). The
macroscopic order that emerges is only possible when these large number of parts are present,
allowing the complex systems to display their self-organizing properties [3, 2].
• Interactions. Interactions are exchanges of energy, matter, or information, whose interaction
mechanisms can be collisions, forces or communication [3]. They are at the heart of complex
systems: without them, the system would be just an aggregation of independent particles, with
no possibility of displaying self-organizing properties.
• Self-organization. The distinguishing feature of complex systems is their dynamic behavior. This
behavior falls between organized simplicity (simple, deterministic) and disorganized complexity
(complex, random). They dynamically "self-organize", creating order out of disorder, contrary
to the natural tendency of systems to follow the 2nd law of thermodynamics (entropy) of total
disorder [1]. To understand and characterize how self-organization happens is the core of the
discipline of complex systems [4]. What represents "order" and "disorder" varies significantly, some
scientists argue that information processing features may be useful to measure order/disorder
[1], while others include notions such as symmetry, organization, periodicity, determinism [3] or
the formation of patterns [5].
• Information-processing. The way how complex systems handle information is the feature
that explains how they operate [3, 1]. Literature explains that natural complex systems compute
information in order to adapt to its environment and learn [3, 1]. The meaning of what precisely
constitutes information and what the complex system does with this information still remains
largely unanswered by the community [1]. The hypothesis is that the individual elements locally
interact, giving rise to local systems states. Local states lead to the emergence of a global state of
the system. Thus, computation is the result of decentralized interactions.
4. Conclusion
This work has presented a preliminary vocabulary of complexity. This vocabulary only considers the
consensual terms found in literature. As a future work, I intend to investigate other terms, such as
emergence, entropy, equifinality, etc. Further, I intend to extend a foundational ontology with this novel
vocabulary in order to improve semantic clarity of these terms.
References
[1] M. Mitchell, Complexity: A Guided Tour, Oxford University Press, Inc., USA, 2009.
[2] Y. Bar-Yam, Dynamics of Complex Systems, Perseus Books, USA, 1997.
[3] J. Ladyman, J. Lambert, K. Wiesner, What is a Complex System?, European Journal for Philosophy
of Science 3 (2013) 33–67. doi:10.1007/s13194-012-0056-8.
[4] H. Sayama, Introduction to the Modeling and Analysis of Complex Systems, Open SUNY Textbooks,
2015.
[5] J. P. Crutchfield, Chapter 3 - What Lies Between Order and Chaos?, in: J. Casti, A. Karlqvist (Eds.),
Art and Complexity, JAI, Amsterdam, 2003, pp. 31–45.