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Theoretical Issues on Systems Science
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Theoretical Issues on Systems Science

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Theory and Methodology".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 24067

Special Issue Editors

Dr. Gianfranco Minati

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Guest Editor
Italian Systems Society, 20161 Milan, Italy
Interests: theoretical issues on systems science; such as logical openness; collective behavior; emergence; dynamic usage of models; meta-structures; multiple-systems and collective beings; quasi-systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Alessandro Giuliani

E-Mail Website
Guest Editor
Environment and Health Department, Istituto Superiore di Sanità, 00161 Rome, Italy
Interests: data analysis; complex systems; systems biology; statistical mechanics
Special Issues, Collections and Topics in MDPI journals
Dr. Andrea Roli

E-Mail Website
Guest Editor
1. Department of Computer Science and Engineering, Campus of Cesena, Alma Mater Studiorum Università di Bologna, I-47522 Cesena, Italy
2. European Centre for Living Technology, I-30123 Venezia, Italy
Interests: complex systems; artificial intelligence; biological models; collective intelligence; swarm robotics; biorobotics

Special Issue Information

Dear Colleagues,

The concept of systems has been elaborated across almost all disciplinary fields, which allows for interdisciplinary approaches. Research on complex systems has focused, for instance, on models and simulations of processes of emergence, self-organization, and chaos theory. The studies on complexity have opened the way towards a Second-Generation General System Theory, as in:

  1. Minati, G., Pessa, E., and Licata, I., (eds.), 2017, Second Generation General System Theory: Perspectives in Philosophy and Approaches in Complex Systems. MDPI, Switzerland https://www.mdpi.com/books/pdfview/book/325
  2. Minati, G., Pessa, E., and Licata, I., (eds.), 2014, Special Issue on Second Generation General System Theory, Systems, MDPI, Switzerland https://www.mdpi.com/journal/systems/special_issues/second-generation-general-system-theory

It is time to theoretically specify various new directions in systems science. The purpose of which is to find higher-level invariants in complex systems, their relations, and their roles in simulations.

Examples of the theoretical issues to be elaborated are:

1) Theoretical incompleteness:

The property of phenomena that are sufficiently incomplete permits the establishment of coherences in multiple equivalences of collective phenomena, allowing for the self-organization and emergence of complex systems.

2) Equivalences:

The incompleteness of multiplicity, identified as necessary for establishing the processes of emergence that would otherwise be blocked, reduced to predictable and computable outcomes, turning off multiplicities of equivalences, real engines of processes of emergence.

3) Multiplicities:

Multiplicity relates to the multiple roles of composing elements that act as simultaneous components of different systems and multiple networks, such as in ecosystems. Another case is the occurrence of multiple localized coherences. Furthermore, multiplicity relates to multiple modeling.

4) Quasi-systems:

Quasi-ness occurs when there are non-equivalent representations of the same system, i.e., a system is not always a system, not always the same system, and not only a system.

5) Tolerance:

As coherence replaces fixed structures in complex systems, versions of the ‘same’ systems may have a sufficient level of equivalence that are able to tolerate and survive structural changes, disappearances and re-appearances of significantly equivalent elements and interactions, and the introduction to new ones.

6) Re-emergence:

Occur in sequences of non-equivalent emergencies, such as the acquisition of defensive behaviors and swarm intelligence by collective systems after their temporary disappearance or disaggregation for any reason.

7) Pending systems:

Potential ‘superimposed’ multiple systems relate to pending, inactivated, implicit interactions waiting for suitable environmental conditions, e.g., energetics, to ‘collapse’ in the activation of one of the pending multiple systems underlying the role of weak forces in deciding new initial conditions and breaking equilibria. The subject may relate to virtual systems.

8) Logical openness:

Relating to the unlimited number of degrees of freedom given by non-completeness when the system is not deterministic or includes the environment that is, in principle, independent, thus making the system incomplete regarding the environmental influence.

9) Meta-structures:

Matter that assumes the mesoscopic level of representation, which involves examining structures and properties of and among clusters.

10) Quantum systems (quantum-like systems that never exhibited non-contextual behavior, have inseparable components, and allow for several different representations).

Examples of issues are:

  • The meaning of causation in entangled quantum systems;
  • The fact that some systems described by deterministic laws, to which it has been added a suitable stochastic ground noise, display behaviors identical to those of quantum systems, and the appearance of long-range correlations and collective effects.

11) Recurrence, self-reflexivity:

Intended as generative properties.

12) Remote synchronization:

Identifies a range of phenomena where two or more entities (nodes in a dynamical network) synchronize, despite the absence of links among them.

13) Chaos theory:

An example of theoretical issues are periodicities, self-similarity, strange attractors, topological invariants, topological mixing, and transitivity.

14) Complex numbers:

The physical meaning of the usage of imaginary variables that not only act as mathematical tricks. For instance, the so-called Fokker–Planck equation (FPE) has a form strongly resembling that of the Schrödinger equation used in quantum mechanics. The two can be made identical by introducing an imaginary time given by ? = i·t.

The purpose of this Special Issue is to review and introduce open theoretical systems issues, while considering their relations and related models.

Contributors are invited to present approaches, cases, models, proposals, and theoretical frameworks to deal with theoretical challenges.

Dr. Gianfranco Minati
Prof. Dr. Alessandro Giuliani
Dr. Andrea Roli
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • chaos
  • coherence
  • equivalence
  • incompleteness
  • meta
  • multiplicity
  • pending systems
  • quantum systems
  • quasi
  • recurrence
  • re-emergence
  • remote
  • tolerance

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (10 papers)

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Research

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10 pages, 349 KiB  
Article
On the Positive Role of Noise and Error in Complex Systems
by Andrea Roli, Michele Braccini and Pasquale Stano
Systems 2024, 12(9), 338; https://doi.org/10.3390/systems12090338 - 1 Sep 2024
Viewed by 1176
Abstract
Noise and error are usually considered to be disturbances negatively affecting the behavior of a system. Nevertheless, from a systemic perspective, taking into account openness and incompleteness of complex systems, noise and error may assume a creative, constructive, and positive role in that [...] Read more.
Noise and error are usually considered to be disturbances negatively affecting the behavior of a system. Nevertheless, from a systemic perspective, taking into account openness and incompleteness of complex systems, noise and error may assume a creative, constructive, and positive role in that they are a source of novelty that can trigger the reorganization of the system, the growth of complexity, and the emergence of new meaning. Examples of this phenomenon can be found in evolutionary phenomena driven by affordances, the formation of new attractors in dynamic systems responding to external perturbations, and improvisation in music. We argue that it is possible to identify general properties that enable the positive effect of noise and errors in complex systems, namely, multilevel organization, redundancy, incompleteness, and criticality. These properties play a major role in living systems and can guide the design of robust and adaptive artificial systems. Full article
(This article belongs to the Special Issue Theoretical Issues on Systems Science)
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16 pages, 702 KiB  
Article
Complexity in Systemic Cognition: Theoretical Explorations with Agent-Based Modeling
by Davide Secchi, Rasmus Gahrn-Andersen and Martin Neumann
Systems 2024, 12(8), 287; https://doi.org/10.3390/systems12080287 - 6 Aug 2024
Cited by 1 | Viewed by 1125
Abstract
This paper presents a systemic view of human cognition that suggests complexityis an essential feature of such a system. It draws on the embodied, distributed, and extended cognition paradigms to outline the elements and the mechanisms that define cognition. In doing so, it [...] Read more.
This paper presents a systemic view of human cognition that suggests complexityis an essential feature of such a system. It draws on the embodied, distributed, and extended cognition paradigms to outline the elements and the mechanisms that define cognition. In doing so, it uses an agent-based computational model (the TS 1.0.5Model) with a focus on learning mechanisms as they reflect on individual competence to gain insights on how cognition works. Results indicate that cognitive dynamics do not depend solely on macro structural elements, nor do they depend uniquely on individual characteristics. Instead, more insights and understanding are available through the consideration of all elements together as they co-evolve and interact over time. This perspective illustrates the essential role of how we define the meso domain and constitutes a clear indication that cognitive systems are indeed complex. Full article
(This article belongs to the Special Issue Theoretical Issues on Systems Science)
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10 pages, 306 KiB  
Article
Emergence in Complex Physiological Processes: The Case of Vitamin B12 Functions in Erythropoiesis
by Francesca Bellazzi and Marta Bertolaso
Systems 2024, 12(4), 131; https://doi.org/10.3390/systems12040131 - 11 Apr 2024
Viewed by 2437
Abstract
In this paper, we will explore the relation between molecular structure and functions displayed by biochemical molecules in complex physiological processes by using tools from the philosophy of science and the philosophy of scientific practice. We will argue that biochemical functions are weakly [...] Read more.
In this paper, we will explore the relation between molecular structure and functions displayed by biochemical molecules in complex physiological processes by using tools from the philosophy of science and the philosophy of scientific practice. We will argue that biochemical functions are weakly emergent from molecular structure by using an account of weak. In order to explore this thesis, we will consider the role of vitamin B12 in contributing to the process of erythropoiesis. The structure of the paper is the following: First, we will consider biochemical functions and why they cannot be easily reduced to their chemical realisers. We will suggest weak emergence as an alternative while also accounting for the relevance of the context, in our case, systemic and organisational. The paper will conclude by considering (1) how the usage of tools from the philosophy of science, such as weak emergence, can aid our understanding of the relations between the components of complex phenomena, such as erythropoiesis, and (2) how the philosophy of scientific practice sheds light on the explanatory role of processes that are dynamically stabilised and the different levels of organisation implied. Full article
(This article belongs to the Special Issue Theoretical Issues on Systems Science)
16 pages, 3764 KiB  
Article
Discrete Event Systems Theory for Fast Stochastic Simulation via Tree Expansion
by Bernard P. Zeigler
Systems 2024, 12(3), 80; https://doi.org/10.3390/systems12030080 - 2 Mar 2024
Viewed by 1616
Abstract
Paratemporal methods based on tree expansion have proven to be effective in efficiently generating the trajectories of stochastic systems. However, combinatorial explosion of branching arising from multiple choice points presents a major hurdle that must be overcome to implement such techniques. In this [...] Read more.
Paratemporal methods based on tree expansion have proven to be effective in efficiently generating the trajectories of stochastic systems. However, combinatorial explosion of branching arising from multiple choice points presents a major hurdle that must be overcome to implement such techniques. In this paper, we tackle this scalability problem by developing a systems theory-based framework covering both conventional and proposed tree expansion algorithms for speeding up discrete event system stochastic simulations while preserving the desired accuracy. An example is discussed to illustrate the tree expansion framework in which a discrete event system specification (DEVS) Markov stochastic model takes the form of a tree isomorphic to a free monoid over the branching alphabet. We derive the computation times for baseline, non-merging, and merging tree expansion algorithms to compute the distribution of output values at any given depth. The results show the remarkable reduction from exponential to polynomial dependence on depth effectuated by node merging. We relate these results to the similarly reduced computation time of binomial coefficients underlying Pascal’s triangle. Finally, we discuss the application of tree expansion to estimating temporal distributions in stochastic simulations involving serial and parallel compositions with potential real-world use cases. Full article
(This article belongs to the Special Issue Theoretical Issues on Systems Science)
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18 pages, 386 KiB  
Article
Theoretical Reflections on Reductionism and Systemic Research Issues: Dark Systems and Systemic Domains
by Gianfranco Minati
Systems 2024, 12(1), 2; https://doi.org/10.3390/systems12010002 - 19 Dec 2023
Viewed by 2813
Abstract
In this article, we explore some theoretical issues related to reductionism and systems. Fundamentally, reductionism neglects that a system can acquire properties. Among various possible reductionist approaches, we consider the reduction of sufficient conditions to necessary conditions in systems, the reduction of emergence [...] Read more.
In this article, we explore some theoretical issues related to reductionism and systems. Fundamentally, reductionism neglects that a system can acquire properties. Among various possible reductionist approaches, we consider the reduction of sufficient conditions to necessary conditions in systems, the reduction of emergence to functioning, and the general linearizability of non-linear systems. Furthermore, we consider the reductionistic deductibility of the macroscopic from the microscopic (as a matter of scalarity without intermediary emergence). We examine “reductionistic interacting” as it relates to multiple sequenced interactions being zippable into a single interaction. We consider the theoretical dynamic mixed usage of reductionism and non-reductionism. We then elaborate on theoretical systemic issues around opaque dark systems (as non-evident systems requiring both change in scale and change sequences). We investigate how a phenomenon can be improperly modeled as a system. This is often undertaken for the convenience of an observer (who takes advantage of the readily available approaches and models). We elaborate on the interdependence and possible equivalence of these phenomena’s theoretical incompleteness and the logical openness of their modeling. We also consider the theoretical issue of systemic domains as space. Here, an entering entity only has access to certain actions and degrees of freedom due to the predominance of a previous systemic phenomenon. We conclude by considering the centrality of theoretical research in systems science. Full article
(This article belongs to the Special Issue Theoretical Issues on Systems Science)
13 pages, 336 KiB  
Article
Systems Precision Medicine: Putting the Pieces Back Together
by Lorenzo Farina
Systems 2023, 11(7), 367; https://doi.org/10.3390/systems11070367 - 18 Jul 2023
Cited by 4 | Viewed by 2032
Abstract
Systems precision medicine is an interdisciplinary approach that recognises the complexity of diseases and emphasises the integration of clinical knowledge, multi-omics data, analytical models, and the expertise of physicians and data analysts to personalise the care pathway in complex diseases, such as cancer [...] Read more.
Systems precision medicine is an interdisciplinary approach that recognises the complexity of diseases and emphasises the integration of clinical knowledge, multi-omics data, analytical models, and the expertise of physicians and data analysts to personalise the care pathway in complex diseases, such as cancer or diabetes. The aim is to gain a comprehensive understanding of diseases by analysing individual components and identifying relevant aspects for therapy and diagnosis. Key components, their interactions and emerging patterns can be studied using statistical, mathematical and computational tools. The combination of data analysis and clinical evaluation is crucial to effective decision-making, emphasising the need for an integrative approach rather than relying on data alone. Therefore, the crucial point discussed in this paper is that the “computational” part and the “artistic” part (i.e., the physician’s intuition) cannot be separated, and therefore, systems precision medicine can be configured as a collective work of art, involving not only different medical professionals but also, and above all, professional data analysts. The work is “artistic” because data and mathematics alone, without medical knowledge of the context, are not enough. But the work is also “collective” in the sense that it must be the place of cultural integration between the professional intuition of the physician, which cannot be translated into mathematical formulas, and the ability to extract information from multi-omics data of the data analysts, who instead use formal and computational mathematical methods. However, to drive the medical revolution and reassemble a patient’s parts, data analysts need to be involved in the hospital context, and precision medicine physicians should embrace data analytical perspectives. This will require ongoing dialogue, new languages of communication, and education that promotes continuous learning and collaboration between professions, fostering a new level of interdisciplinary collaboration for personalised care. Full article
(This article belongs to the Special Issue Theoretical Issues on Systems Science)

Review

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21 pages, 391 KiB  
Review
Chemical Organization Theory as a General Modeling Framework for Self-Sustaining Systems
by Francis Heylighen, Shima Beigi and Tomas Veloz
Systems 2024, 12(4), 111; https://doi.org/10.3390/systems12040111 - 27 Mar 2024
Viewed by 1680
Abstract
This paper summarizes and reviews Chemical Organization Theory (COT), a formalism for the analysis of complex, self-organizing systems across multiple disciplines. Its elements are resources and reactions. A reaction maps a set of resources onto another set, thus representing an elementary process that [...] Read more.
This paper summarizes and reviews Chemical Organization Theory (COT), a formalism for the analysis of complex, self-organizing systems across multiple disciplines. Its elements are resources and reactions. A reaction maps a set of resources onto another set, thus representing an elementary process that transforms resources into new resources. Reaction networks self-organize into invariant subnetworks, called ‘organizations’, which are attractors of their dynamics. These are characterized by closure (no new resources are added) and self-maintenance (no existing resources are lost). Thus, they provide a simple model of autopoiesis: the organization persistently recreates its own components. The resilience of organizations in the face of perturbations depends on properties such as the size of their basin of attraction and the redundancy of their reaction pathways. Application domains of COT include the origin of life, systems biology, cognition, ecology, Gaia theory, sustainability, consciousness, and social systems. Full article
(This article belongs to the Special Issue Theoretical Issues on Systems Science)
16 pages, 735 KiB  
Review
Dynamical Systems Research (DSR) in Psychotherapy: A Comprehensive Review of Empirical Results and Their Clinical Implications
by Giulio de Felice
Systems 2024, 12(2), 54; https://doi.org/10.3390/systems12020054 - 5 Feb 2024
Cited by 3 | Viewed by 2292
Abstract
In psychotherapy research, the first applications of dynamical systems research (DSR) date back to the 1990s. Over time, DSR has developed three main lines of research: the study of oscillations in synchronization; the study of oscillations between stability and flexibility of process variables [...] Read more.
In psychotherapy research, the first applications of dynamical systems research (DSR) date back to the 1990s. Over time, DSR has developed three main lines of research: the study of oscillations in synchronization; the study of oscillations between stability and flexibility of process variables (S–F oscillations); the mathematical modeling to analyze the evolution of psychotherapy process. However, the connections among the empirical results and their implications for psychotherapy practice are unclear. For this reason, for the first time in the literature, this work carries out a comprehensive review of all three lines of research, including the main scientific contributions from the 1990s to the present day. For each line of research, the work critically analyzes the results, proposes future developments, and underlines the connections between empirical results and implications for psychotherapy practice. Furthermore, the work highlights the model of change that emerges from the empirical results, and its clinical correlates. In the conclusions, the author summarizes the results and the evolution of psychotherapy process in accordance with the DSR. Full article
(This article belongs to the Special Issue Theoretical Issues on Systems Science)
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24 pages, 463 KiB  
Review
Universal Complexity Science and Theory of Everything: Challenges and Prospects
by Srdjan Kesić
Systems 2024, 12(1), 29; https://doi.org/10.3390/systems12010029 - 15 Jan 2024
Cited by 1 | Viewed by 6416
Abstract
This article argues that complexity scientists have been searching for a universal complexity in the form of a “theory of everything” since some important theoretical breakthroughs such as Bertalanffy’s general systems theory, Wiener’s cybernetics, chaos theory, synergetics, self-organization, self-organized criticality and complex adaptive [...] Read more.
This article argues that complexity scientists have been searching for a universal complexity in the form of a “theory of everything” since some important theoretical breakthroughs such as Bertalanffy’s general systems theory, Wiener’s cybernetics, chaos theory, synergetics, self-organization, self-organized criticality and complex adaptive systems, which brought the study of complex systems into mainstream science. In this respect, much attention has been paid to the importance of a “reductionist complexity science” or a “reductionist theory of everything”. Alternatively, many scholars strongly argue for a holistic or emergentist “theory of everything”. The unifying characteristic of both attempts to account for complexity is an insistence on one robust explanatory framework to describe almost all natural and socio-technical phenomena. Nevertheless, researchers need to understand the conceptual historical background of “complexity science” in order to understand these longstanding efforts to develop a single all-inclusive theory. In this theoretical overview, I address this underappreciated problem and argue that both accounts of the “theory of everything” seem problematic, as they do not seem to be able to capture the whole of reality. This realization could mean that the idea of a single omnipotent theory falls flat. However, the prospects for a “holistic theory of everything” are much better than a “reductionist theory of everything”. Nonetheless, various forms of contemporary systems thinking and conceptual tools could make the path to the “theory of everything” much more accessible. These new advances in thinking about complexity, such as “Bohr’s complementarity”, Morin’s Complex thinking, and Cabrera’s DSRP theory, might allow the theorists to abandon the EITHER/OR logical operators and start thinking about BOTH/AND operators to seek reconciliation between reductionism and holism, which might lead them to a new “theory of everything”. Full article
(This article belongs to the Special Issue Theoretical Issues on Systems Science)

Other

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12 pages, 1224 KiB  
Opinion
System Science Can Relax the Tension Between Data and Theory
by Alessandro Giuliani
Systems 2024, 12(11), 474; https://doi.org/10.3390/systems12110474 - 6 Nov 2024
Viewed by 660
Abstract
The actual hype around machine learning (ML) methods has pushed the old epistemic struggle between data-driven and theory-driven scientific styles well beyond the academic realm. The potential consequences of the widespread adoption of ML in scientific work have fueled a harsh debate between [...] Read more.
The actual hype around machine learning (ML) methods has pushed the old epistemic struggle between data-driven and theory-driven scientific styles well beyond the academic realm. The potential consequences of the widespread adoption of ML in scientific work have fueled a harsh debate between opponents predicting the decay of basic curiosity-driven science and enthusiasts hoping for the advent of a ‘theory-free’ objective science. In this work, I suggest how the system science style of reasoning could drastically de-potentiate this (sometimes deceptive) opposition through the generation of multi-purpose relational theoretical frames stemming from the network paradigm. The recognition of the virtual non-existence of purely ‘theoryfree’ approaches and the need for a careful balancing of theoretical and empirical contributions is the main claim of the present work. Full article
(This article belongs to the Special Issue Theoretical Issues on Systems Science)
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