scholarly journals Artificial Intelligence for Sustainable Complex Socio-Technical-Economic-Ecosystems.

2021 ◽  
Author(s):  
Alejandro N. Martinez-Garcia
Keyword(s):  
Complex Systems ◽  
Intelligent Agents ◽  
Degrees Of Freedom ◽  
Optimization Problems ◽  
Functional Coupling ◽  
High Stakes ◽  
Nonlinear Phase ◽  
Dynamic Uncertainty ◽  
Zero Sum

The strong couplings among ecological, economic, social and technological processes explains the complexification of human-made systems, and phenomena such as globalization, climate change, the increased urbanization and inequality of human societies, the power of information, and the COVID-19 syndemics. Among complexification’s essential features are non-decomposability, asynchronous behavior, components with many degrees of freedom, increased likelihood of catastrophic events, irreversibility, nonlinear phase spaces with immense combinatorial sizes, and the impossibility of long-term, detailed prediction. Sustainability for complex systems implies enough efficiency to explore and exploit their dynamic phase spaces and enough flexibility to coevolve with their environments. This in turn means solving intractable nonlinear semi-structured dynamic multi-objective optimization problems, with conflicting, incommensurable, non-cooperative objectives and purposes, under dynamic uncertainty, restricted access to materials, energy and information, and a given time horizon, aiming at enhancing the co-evolutionary power of the Biosphere and its human subsystems. Giving the high-stakes, the need for effective, efficient, diverse solutions, their local-global, present-future effects, and their unforeseen short, medium and long-term impacts, achieving sustainable complex systems implies the need for Sustainability-designed Universal Intelligent Agents, harnessing the strong functional coupling between human, artificial and nonhuman biological intelligence in a no-zero-sum game to achieve sustainability.

Late to the Party: The Development of Partisanship in Thailand

2013 ◽  
Vol 1 (2) ◽  
pp. 199-213 ◽  
Author(s):  
Allen Hicken
Keyword(s):  
Political Conflict ◽  
High Stakes ◽  
The North ◽  
Using Data ◽  
Zero Sum

AbstractThis article investigates the emergence of new partisan identities in Thailand. Using data from Thailand's last several elections I trace the emergence of partisanship over the last 15 years, particularly in the north and northeast. The change in the nature of partisanship has helped turn long-simmering tensions into an increasingly intractable political conflict. This mass partisan alignment has upset the equilibrium of Thai politics, transforming what was once an inefficient but modest-stakes game of political horse-trading into a zero sum game with extremely high stakes.

scholarly journals Recent Design Optimization Methods for Energy-Efficient Electric Motors and Derived Requirements for a New Improved Method—Part 1

Proceedings ◽  
2018 ◽  
Vol 2 (22) ◽  
pp. 1400
Author(s):  
Johannes Schmelcher ◽  
Max Kleine Büning ◽  
Kai Kreisköther ◽  
Dieter Gerling ◽  
Achim Kampker
Keyword(s):  
Rare Earth ◽  
Design Optimization ◽  
Energy Efficient ◽  
Degrees Of Freedom ◽  
High Efficiency ◽  
Optimization Problems ◽  
Computing Time ◽  
Optimization Methods ◽  
Electric Motors ◽  
Electric Cars

Energy-efficient electric motors are gathering an increased attention since they are used in electric cars or to reduce operational costs, for instance. Due to their high efficiency, permanent-magnet synchronous motors are used progressively more. However, the need to use rare-earth magnets for such high-efficiency motors is problematic not only in regard to the cost but also in socio-political and environmental aspects. Therefore, an increasing effort has to be put in finding the best design possible. The goals to achieve are, among others, to reduce the amount of rare-earth magnet material but also to increase the efficiency. In the first part of this multipart paper, characteristics of optimization problems in engineering and general methods to solve them are presented. In part two, different approaches to the design optimization problem of electric motors are highlighted. The last part will evaluate the different categories of optimization methods with respect to the criteria: degrees of freedom, computing time and the required user experience. As will be seen, there is a conflict of objectives regarding the criteria mentioned above. Requirements, which a new optimization method has to fulfil in order to solve the conflict of objectives will be presented in this last paper.

scholarly journals Scale-Free Coupled Dynamics in Brain Networks Captured by Bivariate Focus-Based Multifractal Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Orestis Stylianou ◽  
Frigyes Samuel Racz ◽  
Andras Eke ◽  
Peter Mukli
Keyword(s):  
Resting State ◽  
Functional Coupling ◽  
Dependent Manner ◽  
Coupled Dynamics ◽  
Scale Free ◽  
Neural Processes ◽  
Eeg Recordings ◽  
Cortical Regions ◽  
The Brain

While most connectivity studies investigate functional connectivity (FC) in a scale-dependent manner, coupled neural processes may also exhibit broadband dynamics, manifesting as power-law scaling of their measures of interdependence. Here we introduce the bivariate focus-based multifractal (BFMF) analysis as a robust tool for capturing such scale-free relations and use resting-state electroencephalography (EEG) recordings of 12 subjects to demonstrate its performance in reconstructing physiological networks. BFMF was employed to characterize broadband FC between 62 cortical regions in a pairwise manner, with all investigated connections being tested for true bivariate multifractality. EEG channels were also grouped to represent the activity of six resting-state networks (RSNs) in the brain, thus allowing for the analysis of within- and between- RSNs connectivity, separately. Most connections featured true bivariate multifractality, which could be attributed to the genuine scale-free coupling of neural dynamics. Bivariate multifractality showed a characteristic topology over the cortex that was highly concordant among subjects. Long-term autocorrelation was higher in within-RSNs, while the degree of multifractality was generally found stronger in between-RSNs connections. These results offer statistical evidence of the bivariate multifractal nature of functional coupling in the brain and validate BFMF as a robust method to capture such scale-independent coupled dynamics.

scholarly journals Complexity In Psychological Self-Ratings: Implications for research and practice

2020 ◽  
Author(s):  
Merlijn Olthof ◽  
Fred Hasselman ◽  
Anna Lichtwarck-Aschoff
Keyword(s):  
Complex Systems ◽  
Systems Approach ◽  
Complex Dynamics ◽  
Initial Conditions ◽  
Regime Shifts ◽  
Fundamental Aspect ◽  
Time Varying ◽  
Term Prediction ◽  
Sensitive Dependence

Background: Psychopathology research is changing focus from group-based ‘disease models’ to a personalized approach inspired by complex systems theories. This approach, which has already produced novel and valuable insights into the complex nature of psychopathology, often relies on repeated self-ratings of individual patients. So far it has been unknown whether such self-ratings, the presumed observables of the individual patient as a complex system, actually display complex dynamics. We examine this basic assumption of a complex systems approach to psychopathology by testing repeated self-ratings for three markers of complexity: memory, the presence of (time-varying) short- and long-range temporal correlations, regime shifts, transitions between different dynamic regimes, and, sensitive dependence on initial conditions, also known as the ‘butterfly effect’, the divergence of initially similar trajectories.Methods: We analysed repeated self-ratings (1476 time points) from a single patient for the three markers of complexity using Bartels rank test, (partial) autocorrelation functions, time-varying autoregression, a non-stationarity test, change point analysis and the Sugihara-May algorithm.Results: Self-ratings concerning psychological states (e.g., the item ‘I feel down’) exhibited all complexity markers: time-varying short- and long-term memory, multiple regime shifts and sensitive dependence on initial conditions. Unexpectedly, self-ratings concerning physical sensations (e.g., the item ‘I am hungry’) exhibited less complex dynamics and their behaviour was more similar to random variables. Conclusions: Psychological self-ratings display complex dynamics. The presence of complexity in repeated self-ratings means that we have to acknowledge that (1) repeated self-ratings yield a complex pattern of data and not a set of (nearly) independent data points, (2) humans are ‘moving targets’ whose self-ratings display non-stationary change processes including regime shifts, and (3) long-term prediction of individual trajectories may be fundamentally impossible. These findings point to a limitation of popular statistical time series models whose assumptions are violated by the presence of these complexity markers. We conclude that a complex systems approach to mental health should appreciate complexity as a fundamental aspect of psychopathology research by adopting the models and methods of complexity science. Promising first steps in this direction, such as research on real-time process-monitoring, short-term prediction, and just-in-time interventions, are discussed.

scholarly journals THEORETICAL AND METHODOLOGICAL APPROACHES TO THE STUDY OF THE TERRITORIAL SYSTEM OF MONODEVELOPMENT IN GEOGRAPHICAL SPACE

2020 ◽  
pp. 26-34
Author(s):  
Nataliia Smochko
Keyword(s):  
Complex Systems ◽  
Social Systems ◽  
Research Work ◽  
Social Geography ◽  
Hierarchical Levels ◽  
Methodological Approaches ◽  
Traditional Approaches ◽  
Geographical Space ◽  
Innovative Approaches

The purpose of this research work is to analyze modern theoretical and methodological approaches to the study of territorial systems of monodevelopment in the theory of social geography. Method. General scientific methods, including analysis, scientific synthesis, analytical method, methods of comparison and generalization were used in the study. Scientific novelty. The article reveals traditional and innovative approaches to identifying and defining the territorial system of mono-development in the geographical space. In substantiating the application of approaches, we used the work of scientists and geographers, who took them into account in the study of complex systems. It has been determined that the leading and traditional approaches in socio-geographical research are historical-geographical (retrospective) and territorial (geospatial), which should be combined with genetic. According to which all geographical phenomena have been considered as processes that have their genesis, dynamics, differences, patterns spatial distribution. To study the processes of system formation, a comprehensive approach is important. It provides a comprehensive analysis of the development of the main factors in the formation of modern socio-economic processes in the regions. The system approach allows to consider functioning and development of the territorial monosystem and its basic types as systems of the territorial organization of a society at various hierarchical levels, to open their integrity and the mechanisms providing effective management of such monodevelopment. At the same time, it has been found that not all the outlined approaches of complex systems can be used to study monosystems in the form in which they were used previously. This is because in the study of systems in retrospect, the application of approaches was focused on the analysis of the structure of the studied objects and the variety of processes that took place between the elements of the studied systems. In the study of monosystems, the researcher should be interested in their development to bifurcation moments and the conditions for further preservation of monosystems. This means that traditional approaches, such as historical-geographical (retrospective) and territorial (geospatial) should be modified to adapt to these tasks. It is important to use innovative approaches: cluster (formation of so-called network structures), behaviorist (explanation of the territorial identity of the monosystem), participatory (strategic planning of the territorial development of the monosystem). Only by combining a variety of approaches will it be possible to obtain a synergistic effect and form a synergistic approach that will provide additional benefits in the study of monosystems and the processes of their functioning. Practical meaning. The results of this study contribute to a deeper socio-geographical understanding of the processes of monodevelopment, their genesis, features of their course and provide an opportunity to model the long-term development of territorial social systems, to achieve expected results due to long-term transformation. They can be used for further study of monosystems of different hierarchical levels, as well as for the development of practical recommendations and programs for the development of individual monoterritories.

scholarly journals The Paris Agreement: Historic Breakthrough or High Stakes Experiment?

Climate Law ◽  
2016 ◽  
Vol 6 (1-2) ◽  
pp. 1-20 ◽  
Author(s):  
Meinhard Doelle
Keyword(s):  
Kyoto Protocol ◽  
Paris Agreement ◽  
Climate Regime ◽  
Top Down ◽  
High Stakes ◽  
Flexible Approach ◽  
Climate Negotiations ◽  
Loss And Damage ◽  
Self Differentiation

This article offers an overview of the two key outcomes of the 2015 Paris climate negotiations, the Paris cop decision, and the Paris Agreement. Collectively, they chart a new course for the un climate regime that started in earnest in Copenhagen in 2009. The Paris Agreement represents a path away from the top-down approach and rigid differentiation among parties reflected in the Kyoto Protocol, toward a bottom-up and flexible approach focused on collective long-term goals and principles. It represents an approach to reaching these long-term goals that is focused on self-differentiation, support, transparency, and review. The article highlights the key elements of the agreement reached in Paris, including its approach to mitigation, adaptation, loss and damage, finance, transparency, and compliance.

scholarly journals Opportunities and challenges of using socially intelligent agents: increasing interaction and school participation for children suffering from a long-term illness

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Eva Mårell-Olsson ◽  
Thomas Mejtoft ◽  
Sofia Tovedal ◽  
Ulrik Söderström
Keyword(s):  
Intelligent Agents ◽  
Design Methodology ◽  
Holistic Approach ◽  
Negative Effects ◽  
Content Type ◽  
Medical Needs ◽  
Societal Benefits ◽  
School Participation

PurposeChildren suffering from cancer or cardiovascular disease, who need extended periods of treatment in hospitals, are subjected to multiple hardships apart from the physical implications, for example, experienced isolation and disrupted social and academic development. This has negative effects long after the child's recovery from the illness. The purpose of this paper is to examine the non-medical needs of children suffering from a long-term illness, as well as research the field of artificial intelligence (AI) – more specifically, the use of socially intelligent agents (SIAs) – in order to study how technology can enhance children's interaction, participation and quality of life.Design/methodology/approachInterviews were performed with experts in three fields: housing manager for hospitalized children, a professor in computing science and researcher in AI, and an engineer and developer at a tech company.FindingsIt is important for children to be able to take control of the narrative by using an SIA to support the documentation of their period of illness, for example. This could serve as a way of processing emotions, documenting educational development or keeping a reference for later in life. The findings also show that the societal benefits of AI include automating mundane tasks and recognizing patterns.Originality/valueThe originality of this study concerns the holistic approach of increasing the knowledge and understanding of these children's specific needs and challenges, particularly regarding their participation and interaction with teachers and friends at school, using an SIA.

Visualising the invisible: performing chaos theory

Leonardo ◽  
2020 ◽  
pp. 1-8
Author(s):  
Emma Weitkamp
Keyword(s):  
Complex Systems ◽  
Chaos Theory ◽  
Initial Conditions ◽  
Starting Point ◽  
Weather And Climate ◽  
Butterfly Effect ◽  
Long Term Behavior ◽  
The Invisible

Edward Lorenz, the pioneering figure in the field of chaos theory coined the phrase “butterfly effect” and posed the famous question “Does the flap of a butterfly's wings in Brazil set off a tornado in Texas?” In posing the question, Lorenz sought to highlight the intrinsic difficulty of predicting the long term behavior of complex systems that are sensitive to initial conditions, like, for example, the weather and climate; these systems are often referred to as chaotic. Taking Lorenz' butterfly as a starting point, Chaos Cabaret sought to explore the nuances of chaos theory through performance and music.

Reliability Optimization of Complex Systems Using Cuckoo Search Algorithm

2017 ◽  
pp. 94-110 ◽  
Author(s):  
Anuj Kumar ◽  
Sangeeta Pant ◽  
S. B. Singh
Keyword(s):  
Complex Systems ◽  
Life Support ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Reliability Optimization ◽  
Space Capsule ◽  
Metaheuristic Techniques

In this chapter, authors briefly discussed about the classification of reliability optimization problems and their nature. Background of reliability and optimization has also been provided separately so that one can clearly understand the basic terminology used in the field of reliability optimization. Classification of various optimization techniques have also been discussed by the authors. Few metaheuristic techniques related to reliability optimization problems like Genetic Algorithm (GA), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) have been discussed in brief. Thereafter, authors have discussed about Cuckoo Search Algorithm (CSA) which is the main focus of this chapter. Finally, Cuckoo Search Algorithm has been applied for solving reliability optimization problems of two complex systems namely complex bridge system and life support system in space capsule. Simulation results and conclusion have been presented in the last followed by the references.

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