Social Self-Organization: Agent-Based Simulations and Experiments to Study Emergent Social Behavior

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To get access to this content you need the following product:. Springer Professional "Technik" Online-Abonnement. Nagano S Modeling the model organism Dictyostelium discoideum. Dev Growth Differ 42 6 — CrossRef. Vasieva O, Vasiev B Mathematical modeling in developmental biology. Reproduction 6 :R—R CrossRef. Dev Biol 1 —36 CrossRef. Proteomics 10 13 — CrossRef. Trends Gene 27 2 —54 CrossRef. Dev Biol 2 — CrossRef.

Dirk Helbing, Dr. rer. nat., Dr. h.c.

Microbiology 2 — CrossRef. Maeda Y Regulation of growth, differentiation in Dictyostelium. Int Rev Cytol — CrossRef.

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Kessin RH Dictyostelium : evolution, cell biology, and the development of multicellularity. Mol Biol Cell 25 5 — CrossRef. Mackay SA Computer simulation of aggregation in Dictyostelium discoideum. J Cell Sci 33 1 :1— Loomis W Dictyostelium discoideum : a developmental system. Elsevier, Amsterdam. J Cell Sci 21 2 — J Cell Sci — J Cell Sci 2 — CrossRef. J Cell Sci 21 — CrossRef.

Microbiology 9 — CrossRef. Williams JG Dictyostelium finds new roles to model. Genetics 3 — CrossRef. Mol Biol Cell 13 2 — CrossRef. The populational distribution of the capacity to initiate aggregation. Biol Bull 2 — CrossRef.

Agent-Based Simulations and Experiments to Study Emergent Social Behavior

Dev Growth Differ 53 4 — CrossRef. J Theor Biol 3 — CrossRef. Microbiology 11 — CrossRef. Microbiology — Levchenko A, Iglesias PA Models of eukaryotic gradient sensing: application to chemotaxis of amoebae and neutrophils. Biophys J 82 1 —63 CrossRef. Krishnan J, Iglesias PA Analysis of the signal transduction properties of a module of spatial sensing in eukaryotic chemotaxis. SWARM the 2nd international symposium on swarm behaviour and bio-inspired robotics. Thorough analyses are performed using universal principles of field-based self-organization on various scales, starting from the micro level, i.

In fact, the proposition that the physical manifestation of consciousness is a bioelectromagnetic field BEM that exhibits wave-mechanical dynamics has profound implications for our understanding of the phenomenon of consciousness. At least theoretically, we can acknowledge and arrive at the viewpoint that societies can also be understood as collective consciousness processes emerging from the coordinated behaviour of the conscious and subconscious bioelectromagnetic brain fields of individual members of society.

In this way, we can hypothetically admit that emergent social behaviour could be at least partly associated with some coherent, collective, bioelectromagnetic brain field, characterized by some synchronous collective mind state processes and, therefore, can inherit some degree of wave-like excitation behaviour. We have to be aware that studying the mind-field basis of social cognition and interaction in terms of two- or multi-person neuroscience may shift the focus of traditional research into social communication from basic sensory functions in individual subjects toward the study of interconnected mind-fields.

From another perspective, social networks, digital services and the network economy at large, are highly heterogeneous with many links and complex interrelations. Uncoupled and indirect interactions among agents require the ability to affect and perceive information in a field-broadcasted context. In this sense, there is a need to look for ways to model the information network as a virtual information field, where each network node receives pervasive broadcasted information-field values.

Such an approach is targeted to enforce indirect and uncoupled contextual interactions among agents in order to represent contextual broadcasted information in a form locally accessible and immediately usable by network agents. The implications of collective behaviour modelling in the simulated agent-based social mediums play a paramount role in achieving a better understanding of the behaviour of modern digitally interconnected economic systems.

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It provides a unique possibility to define some novel ways to manage the core individual and collective parameters, which impede or enable the observation of local and nonlocal emergent complex social phenomena. In a wider perspective, such modelling provides means to simulate and investigate various sensitivity, fragility and contagion processes in different social mediums.

In this way, via agent states-related diffusion properties, we could investigate complex economic phenomena like the spread of stock market crashes, currency crises, speculative oscillations bubbles and crashes , social unrest, recessionary effects, sovereign defaults, etc. All these effects are closely associated with social fragility, which is affected by and follows seasonal, production, political, business, financial and other cycles. However, there is a long way to go and the author believes this manuscript can contribute in that way via some of the original conceptual insights, experimental frameworks and social simulation models provided.

Introduction to Complexity: Models of Biological Self-Organization

The multidisciplinary OSIMAS paradigm, not only via some theoretical insights but also via an empirical and simulation framework, contributes to a new way for modelling the complex dynamics of individual and collective mind states, where emergent complex social behaviour is understood as a consequence of coherent individual mind-field effects. We hope that approaches based on the proposed research framework will help to reveal new frontiers of multidisciplinary research.

However, we also admit that extended additional conceptual, experimental and simulation research needs to be done to examine, in detail, the issues and criteria that will help improve the OSIMAS paradigm and associated models. This could yield new knowledge and surprising perspectives, allowing a better understanding of social agents, their social organization principles and the corresponding simulation models of individual and collective behavioural patterns.

Social Self-Organization

In a way, this book with its presented pioneering paradigm is just a beginning, which reveals a perspective of a vast new multidisciplinary research area. Hence, because of its highly multidisciplinary nature, this book might be of interest to scholars in many disciplines, e.


Students from various disciplines may also find a lot of inspiring ideas here about some unconventional research topics. The author is grateful to all who have participated in the project and preparation of the book as well. Especially during the course of the related studies, the author is thankful for the collaboration to prof. Sarunas Raudys, prof.

James F. Glazebrook, and prof. Dragan Milovanovic, who have actively participated in the research process, reviewed the monograph and prepared their substantial contribution in some Chapters and Appendixes. I am thankfull for the fruitfull discussions from David W.

Volume 11 Issue 17 (2016)

Thanks are due also to anonymous reviewers who helped to improve the final stages of the book prepraration. I am also thankful for the proofreading efforts, and suggested edits by the publisher. In general, the content of this book is organized so that the reader would first become familiar with the philosophical and conceptual ideas stemming from the great diversity of related research approaches.

Afterwards it introduces the OSIMAS research conceptual framework, which proceeds with the experimental chapters that pertain to the neuroscience related EEG electroencephalography research of human brain oscillations in the form of brainwaves. In fact, the structure of this book has been partly formed by a summation and adaptation of the earlier publications. Therefore, some chapters have their own line of thought and can be read separately from the rest of the book. However, all the chapters are closely related to the OSIMAS paradigm and follow its development in a chronological way.

Individual-Based Models

Brief comments regarding the content are provided below, and the first synopsis chapter explains the multidisciplinary scope and major aims of the book in more detail. It briefly introduces the related cross-disciplinary research approaches. The second chapter is mainly focused on i identifying the general properties of information-based economic systems, ii ways to model the emergent and self-organizing features of social networks, and iii discussion on how to simulate complex economic systems using the field-based approach and multi-agent platforms. This chapter provides some ideas and examples on how, not only the communication mechanism, but also the social agents can be simulated as oscillating processes.

The fourth chapter not only comments on the major conceptual assumptions of the proposed OSIMAS paradigm, but also presents an electroencephalography EEG -based inductive experimental validation framework and some empirical results to validate the major OSIMAS assumptions from the point of view of some baseline individual neurodynamics. In other words, here is presented the experimental neuroscience based research framework and some experimental evidences of the oscillatory nature of social agents as approximations of real humans. In this regard, we noticed from the neuroscience domain, that basic mind states, which directly influence human behavior, can be characterized by the specific brainwave oscillations.

For the experimental validation or disproof of the biologically inspired OSIMAS paradigm we have designed a framework of baseline individual and group-wide EEG based experiments. Initial baseline individual tests of spectral cross-correlations of EEG-recorded brainwave patterns for some mental states have been provided in this chapter. Investigation and further refinements of this biologically inspired experimental model helped to define the features of our constructed oscillating agent model OAM in the OSIMAS paradigm.

Hence, the oscillation based modelling of human brain EEG signals oscillations, using a refined Kuramoto model, not only directly demonstrates validity of the OSIMAS premises but also helps to specify the OAM, but also significantly contributes to EEG signals prognostication research, which is the major topic of this particular direction of neuroscience research. The sixth chapter describes a conceptually novel modelling approach, based on quantum theory, to the basic human mind states as systems of coherent oscillation.

The proposed quantum mechanics-based approach reveals possibilities of employing wave functions and quantum operators for a stylized description of basic mind states and the transitions between them in the OAM. The basic mind states are defined using experimentally observed EEG spectra, i. Such an approach provides an opportunity to model the dynamics of the basic mind states by employing stylized oscillation-based representations of the characteristic EEG power spectral density PSD distributions of the brainwaves observed in experiments.

In the seventh chapter, a description and some explanatory sources pertaining to the oscillating agent model OAM are provided, which are an intrinsic part of the oscillations based OSIMAS paradigm. The OAM models a social agent in terms of a set of basic mind-brain states and the transitions between them.