Morphogenesis-Emergence-Adaptation model, Dynamical systems modeling, Complex network modeling

An exploration of models for understanding complex systems. One theoretical model proposes that continuous structural self-organization in the brain, or morphogenesis, gives rise to adaptive behavior. Other approaches use dynamical systems theory, complex network theory, and system dynamics to model phenomena from social contracts in simulated agent societies to the resilience of urban infrastructure. These frameworks provide methods to investigate features like self-organization and emergence, offering insights into system behavior.

A theoretical model describes neuronal morphogenesis as continuous structural self-organization, generating functional order. This model suggests adaptive behavior arises from the brain's perpetual morphogenesis, combining principles of plasticity, self-organization, and free energy. Researchers also presented the Biofield-Tissue Tensegrity Matrix (BTTM) theoretical model.

Dynamical systems theory forms the basis for rule-based complex system models, examining how systems change over time and addressing organized complexity, as seen in population growth or celestial mechanics. Complex network theory models complex systems by portraying elements as nodes and their connections as edges, allowing for examination of nonlinear dynamics, self-organization, and emergence. Conventional linear modeling paradigms prove insufficient for describing subtle, nonlocal, and memory-dependent behaviors typical of complex systems across diverse fields.

Researchers developed a simulated agent society where complex social relationships evolve. Agents within this environment possess psychological drives and operate in a sandbox survival setting, building on previous Large Language Model agent designs. In this simulated agent society, social contracts emerged, resulting in the authorization of an absolute sovereign and the establishment of a peaceful commonwealth based on mutual cooperation. Within these simulations, agents participate in unrestrained conflict, and Large Language Models model social dynamics.

A study applied Actor-Network Theory (ANT) to investigate m-learning integration within university organizations. The research employed a participative fieldwork approach, utilizing ANT's 'points of passage' concept, which was applied and refined over a multi-year study. Research systematically reviews the derivation of classical epidemiological models, specifically their origin from simple agent-based dynamics. A study connects population evolution with the dynamics of contact distribution, demonstrating how individual behaviors influence macroscopic epidemiological trends. A study examines Nature-Inspired Solutions (NiS) to support resilience in architecture, urban design, and planning. These solutions draw design principles from natural systems to create resilient infrastructure and settlements.

Researchers developed a system dynamics-based framework to identify methods for improving urban gas infrastructure resilience in new districts, supporting proactive planning. A system dynamics model's baseline scenario showed limitations in the system's capacity for natural evolution. This scenario resulted in slow improvements for social and environmental resilience, and insufficient economic resilience, contributing to low overall urban ecological resilience. Research indicates social communication is a complex concept, more amenable to description than strict definition. Understanding this concept assists in developing assessment and intervention models for individual children. Advanced mathematical frameworks and AI techniques support decision-making in complex situations.

Sources

NEURONAL MORPHOGENESIS AND THE EMERGENCE OF ADAPTIVE BEHAVIOR
The paper explores the relationship between neuronal morphogenesis and the emergence of adaptive behavior from an interdisciplinary perspective that integrates developmental biology, neuroscience, complex systems theory, and cognitive sciences. It is argued that neuronal morphogenesis represents a process of continuous structural self-organization, which generates functional order and allows the emergence of cognitive and behavioral processes. The proposed theoretical model - Morphogenesis-Emergence-Adaptation - describes the circular coevolution between form, function and dynamics,…
EDITORIAL ARTICLE OF SPECIAL ISSUE: PART I-B SERIES MATHEMATICAL MODELING OF COMPLEX SYSTEMS: FRACTALS-FRACTIONAL-ITÔ-DEs-WAVELET-ENTROPY-AI-BASED THEORIES, ANALYSES AND APPLICATIONS
Dynamical systems theory as the foundation of rule-based models of complex systems takes into consideration not only the static properties of observations but also the way systems evolve over time in response to problems of organized complexity. From population growth to swinging pendula through the movement of celestial bodies in the universe, examples of dynamical and complex systems are abundant in the form of a system whose state can exclusively specified by a set of variables and whose behaviors can be described through pre-defined rules. Conventional linear modeling paradigms may fall…
Artificial Leviathan: exploring social evolution of LLM agents through the lens of hobbesian social contract theory
Introduction The emergence of Large Language Models (LLMs) and advancements in Artificial Intelligence (AI) offer an opportunity for computational social science research at scale. Building upon prior explorations of LLM agent design, our work introduces a simulated agent society where complex social relationships dynamically form and evolve over time. Methods Agents are given psychological drives and placed in a sandbox survival environment. We conduct an evaluation of the agent society through the lens of Thomas Hobbes’s seminal Social Contract Theory (SCT), analyzing whether agents seek to…
Risk-based sensitivity analysis of urban gas infrastructure in new district planning
Urban gas infrastructure resilience is critical for public safety, yet rapidly expanding networks face increasing vulnerability. This study develops a system dynamics-based framework to identify key leverage points for enhancing gas infrastructure resilience in new urban districts. Using a three-tier indicator system of 32 risk factors across four dimensions, analytic hierarchy process weighting is integrated with system dynamics modeling in a case study of a new district in China. Sensitivity analysis reveals that system's inherent resilience contributes most significantly, with the…
Potentially disruptive IS innovation in UK higher education institutions: an actor-network theory analysis of the embedding of m-learning
The use of mobile devices to support students’ learning experiences is a growing area of interest in higher education (Wankel & Blessinger, 2013). This study adopts an ‘umbrella’ term of m-learning to consider the use of mobile and wireless technologies to support students in a blended learning environment. Whilst m-learning pedagogy has received considerable attention (e.g. Attewell, 2005, Sharples et. al. 2007, Kukulska-Hulme, 2012), the process of adopting this potentially disruptive innovation within universities has been neglected. This study addresses this gap by attempting to…
Derivation of macroscopic epidemic models from multi-agent systems
We present a systematic review of some basic results on the derivation of classical epidemiological models from simple agent-based dynamics. The evolution of large populations is coupled with the dynamics of the contact distribution, providing insights into how individual behaviours impact macroscopic epidemiological trends. The resulting set of equations incorporates local characteristics of the operator governing the emergence of a family of contact distributions. To validate the proposed approach, we provide several numerical results based on asymptotic-preserving methods, demonstrating…
Reimagining Coastal Resilience: Integrating Nature-Inspired Solutions into Architecture and Urban Design Practice
Coastal urban environments are increasingly exposed to natural hazards, including storm surges, tsunamis, coastal erosion, and flooding, which threaten lives, livelihoods, and infrastructure. Despite their widespread use, conventional hard and soft engineering measures have often proved insufficient to address the escalating risks posed by climate change and rapid urbanisation. This study explores the potential of Nature-Inspired Solutions (NiS) as a complementary pathway to advance resilience in architecture, urban design, and planning. Unlike Nature-Based Solutions that utilise existing…
System dynamics-based scenario analysis of infrastructure investment and urban ecological resilience of Henan Province, China
The feedback mechanisms between infrastructure investment and ecological resilience are complex, and there is still a lack of in-depth understanding of their coupling effects in academic circles. To systematically evaluate the combined impact of infrastructure investment on socio -economic -ecological systems, this study takes Henan Province as the research object and constructs a dynamic simulation model incorporating infrastructure investment, environmental governance, industrial development, and social service mechanisms on the basis of the system dynamics method. Focusing on five core…
An exploration of social communication in the clinical and educational context
The term ‘social communication’ is used within UK health and education services across a number of professional groups. However, it is unclear what social communication is and how professionals should address the needs of children and young people described as having social communication deficits. This thesis explores the understanding and use of the term ‘social communication’ in clinical and educational contexts. A broadly phenomenological approach was adopted in this mixed methods study to consider professionals’ views regarding the concept of ‘social communication’. Five data sets were…

Also this week

International Journal of Complementary & Alternative Medicine

Full transcript

How can a system's behavior be adaptive if its very structure is always changing? This question is at the center of several models we're looking at for this issue of ComplexityPod. We begin with a framework for how the brain generates behavior through perpetual self-organization. This week's papers are looking at different ways to model complex systems—everything from biology to urban planning. Which makes sense, because conventional models often can't keep up. They don't capture how these systems change over time or have memory of past events. Exactly. So one foundational approach is dynamical systems theory. It provides rules for how a system evolves over time, which gets at that organized complexity you mentioned. So that's the math behind things like population growth curves or even tracking planets. Right. And another approach is complex network theory. You represent the parts of a system as nodes and their connections as edges. This lets you study things like self-organization and how new behaviors just seem to emerge from the interactions. And these emergent behaviors are really the core of it. So let's look at some examples. There's one model for how the brain works. Yes, the Morphogenesis-Emergence-Adaptation model. It proposes that the brain is in a state of continuous structural self-organization—that neuronal morphogenesis is what generates functional order. So the brain’s physical form and its function are constantly co-evolving. The process of the brain rebuilding itself *is* how it adapts. And that idea of emerging social function is explored in other papers too. One thesis looks at social communication in children, suggesting it's a concept to be described rather than rigidly defined, which could help create better interventions. And another piece of research takes that to a pretty wild conclusion with a simulated agent society. They put these agents with psychological drives into a sandbox survival world. And what happened was that social contracts started to form. The agents eventually authorized an absolute sovereign to create a peaceful commonwealth based on cooperation. So order emerged from potential chaos, but it required ceding power. And this same technique, agent-based modeling, is also being used to understand epidemiology. Correct. A review looks at how classical epidemiological models can be derived from these simple agent-based dynamics. It connects the dynamics of how contacts are distributed in a population with the evolution of that population. It’s a way to see how individual choices and behaviors add up to the large-scale trends we see during an outbreak. These models are also being used for planning and resilience. One study used system dynamics modeling to find leverage points for improving gas infrastructure resilience in new urban districts. And the most significant factor they found was the system's inherent resilience, not any single, small fix. Another study is looking at what it calls 'Nature-Inspired Solutions' for architecture and urban design, deriving principles for resilience from natural systems. But that doesn't always work. A separate analysis, also using a system dynamics model, found that in its baseline scenario, a system's capacity for natural evolution was limited. Social and environmental resilience improved slowly, but economic resilience was insufficient. Right, leading to low overall urban resilience. It's a trade-off. Then there are organizational systems. Researchers applied Actor-Network Theory to see how mobile learning gets embedded in universities. They used a concept called 'points of passage' to do the fieldwork. It helps trace how a technology actually finds its place within an organization. And there were a few other items. Advanced mathematical frameworks and AI are being used to enhance decision-making in complex situations. And on the flip side of that peaceful commonwealth simulation, other simulations showed agents just engaging in unrestrained conflict. Large Language Models are also being used now to model social dynamics. And finally, researchers presented a theoretical model called the Biofield-Tissue Tensegrity Matrix. We'll have more research summaries in our next issue. Thanks for listening to ComplexityPod.