Complex Computational Ecosystems

Complex Computational Ecosystems PDF

Author: Pierre Collet

Publisher: Springer Nature

Published: 2023-10-25

Total Pages: 245

ISBN-13: 3031443551

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This book constitutes the proceedings of the First International Conference on Complex Computational Ecosystems, CCE 2023, held in Baku, Azerbaijan, during April 25–27, 2023. The 16 full papers and the 4 keynote abstracts included in this volume were carefully reviewed and selected from 46 submissions. They explore trans-disciplinary challenges that crossed theoretical questions with empirical observations of multi-level and multi-modal computational ecosystems.

Complexity and Ecosystem Management

Complexity and Ecosystem Management PDF

Author: Marco Janssen

Publisher: Edward Elgar Publishing

Published: 2002-01-01

Total Pages: 366

ISBN-13: 9781781957240

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The quality of ecosystems is affected by the actions of different stakeholders who use them in a variety of ways. In order to understand this complex relationship between humans and nature, it is vital to understand the complexity of the interacting agents. The authors in this book attempt to do this by applying multi-agent systems to the problems of ecosystem management. The multi-agent approach to ecosystem management is a relatively new and rapidly developing field which takes a formal computational approach towards the interaction of humans with their environment. The authors highlight some of the promising new methodologies which are emerging in the field from disciplines such as computer science and computational social science. They move on to address a number of important topics including diffusion processes, common-pool resources, land use change and the participatory use of models, in an attempt to solve contemporary management issues. They clearly demonstrate the potential utility of multi-agent systems in the context of theoretical problems and practical case studies.

Computing Research for Sustainability

Computing Research for Sustainability PDF

Author: National Research Council

Publisher: National Academies Press

Published: 2012-08-06

Total Pages: 172

ISBN-13: 0309257581

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A broad and growing literature describes the deep and multidisciplinary nature of the sustainability challenges faced by the United States and the world. Despite the profound technical challenges involved, sustainability is not, at its root, a technical problem, nor will merely technical solutions be sufficient. Instead, deep economic, political, and cultural adjustments will ultimately be required, along with a major, long-term commitment in each sphere to deploy the requisite technical solutions at scale. Nevertheless, technological advances and enablers have a clear role in supporting such change, and information technology (IT) is a natural bridge between technical and social solutions because it can offer improved communication and transparency for fostering the necessary economic, political, and cultural adjustments. Moreover, IT is at the heart of nearly every large-scale socioeconomic system-including systems for finance, manufacturing, and the generation and distribution of energy-and so sustainability-focused changes in those systems are inextricably linked with advances in IT. The focus of Computing Research for Sustainability is "greening through IT," the application of computing to promote sustainability broadly. The aim of this report is twofold: to shine a spotlight on areas where IT innovation and computer science (CS) research can help, and to urge the computing research community to bring its approaches and methodologies to bear on these pressing global challenges. Computing Research for Sustainability focuses on addressing medium- and long-term challenges in a way that would have significant, measurable impact. The findings and recommended principles of the Committee on Computing Research for Environmental and Societal Sustainability concern four areas: (1) the relevance of IT and CS to sustainability; (2) the value of the CS approach to problem solving, particularly as it pertains to sustainability challenges; (3) key CS research areas; and (4) strategy and pragmatic approaches for CS research on sustainability.

Transforming Public-Private Ecosystems

Transforming Public-Private Ecosystems PDF

Author: William B. Rouse

Publisher: Oxford University Press

Published: 2022-06-23

Total Pages: 273

ISBN-13: 0192691724

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Public-private collaborations are central to the functioning and provisioning of most essential ecosystems. Ecosystems such as security, healthcare, education, and the environment face challenges of governance, diverse constituencies, numerous advocacy organizations, incompatible outcome metrics, and persistent media attention, to name a few. There is a wide range of public and private players involved in operating, sustaining, and investing in these ecosystems, including stakeholders from government, industry, academia, non-governmental organizations, and the general public. Fundamental change requires understanding a wide range of interests and accommodating change strategies accordingly. The challenges of transforming these ecosystems would easily qualify as “wicked problems”; social or cultural problems laced with incomplete or contradictory knowledge, large numbers of people and opinions, substantial economic burdens, and inextricable connections with other issues. Transforming Public-Private Ecosystems addresses these challenges for the four important ecosystems of national security, healthcare delivery, higher education, and energy and climate, and provides an integrated perspective for understanding and enabling change.

The Ecology of Computation

The Ecology of Computation PDF

Author: Bernardo A. Huberman

Publisher:

Published: 1988

Total Pages: 358

ISBN-13:

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Propelled by advances in software design and increasing connectivity, distributed computational systems are acquiring characteristics reminiscent of social and biological organizations. This volume is a collection of articles dealing with the nature, design and implementation of these open computational systems. Although varied in their approach and methodology, the articles are related by the goal of understanding and building computational ecologies. They are grouped in three major sections. The first deals with general issues underlying open systems, studies of computational ecologies, and their similarities with social organizations. The second part deals with actual implementations of distributed computation, and the third discusses the overriding problem of designing suitable languages for open systems. All the articles are highly interdisciplinary, emphasizing the application of ecological ideas, game theory, market mechanisms, and evolutionary biology in the study of open systems.

Understanding Complex Ecosystem Dynamics

Understanding Complex Ecosystem Dynamics PDF

Author: William S. Yackinous

Publisher: Academic Press

Published: 2015-06-03

Total Pages: 435

ISBN-13: 0128020636

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Understanding Complex Ecosystem Dynamics: A Systems and Engineering Perspective takes a fresh, interdisciplinary perspective on complex system dynamics, beginning with a discussion of relevant systems and engineering skills and practices, including an explanation of the systems approach and its major elements. From this perspective, the author formulates an ecosystem dynamics functionality-based framework to guide ecological investigations. Next, because complex system theory (across many subject matter areas) is crucial to the work of this book, relevant network theory, nonlinear dynamics theory, cellular automata theory, and roughness (fractal) theory is covered in some detail. This material serves as an important resource as the book proceeds. In the context of all of the foregoing discussion and investigation, a view of the characteristics of ecological network dynamics is constructed. This view, in turn, is the basis for the central hypothesis of the book, i.e., ecological networks are ever-changing networks with propagation dynamics that are punctuated, local-to-global, and perhaps most importantly fractal. To analyze and fully test this hypothesis, an innovative ecological network dynamics model is defined, designed, and developed. The modeling approach, which seeks to emulate features of real-world ecological networks, does not make a priori assumptions about ecological network dynamics, but rather lets the dynamics develop as the model simulation runs. Model analysis results corroborate the central hypothesis. Additional important insights and principles are suggested by the model analysis results and by the other supporting investigations of this book – and can serve as a basis for going-forward complex system dynamics research, not only for ecological systems but for complex systems in general. Provides a fresh interdisciplinary perspective, offers a broad integrated development, and contains many new ideas Clearly explains the elements of the systems approach and applies them throughout the book Takes on the challenging and open issues of complex system network dynamics Develops and utilizes a new, innovative ecosystem dynamics modeling approach Contains over 135 graphic illustrations to help the reader visualize and understand important concepts

First Complex Systems Digital Campus World E-Conference 2015

First Complex Systems Digital Campus World E-Conference 2015 PDF

Author: Paul Bourgine

Publisher: Springer

Published: 2016-12-24

Total Pages: 407

ISBN-13: 3319459015

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This book contains the proceedings as well as invited papers for the first annual conference of the UNESCO Unitwin Complex System Digital Campus (CSDC), which is an international initiative gathering 120 Universities on four continents, and structured in ten E-Departments. First Complex Systems Digital Campus World E-Conference 2015 features chapters from the latest research results on theoretical questions of complex systems and their experimental domains. The content contained bridges the gap between the individual and the collective within complex systems science and new integrative sciences on topics such as: genes to organisms to ecosystems, atoms to materials to products, and digital media to the Internet. The conference breaks new ground through a dedicated video-conferencing system – a concept at the heart of the international UNESCO UniTwin, embracing scientists from low-income and distant countries. This book promotes an integrated system of research, education, and training. It also aims at contributing to global development by taking into account its social, economic, and cultural dimensions. First Complex Systems Digital Campus World E-Conference 2015 will appeal to students and researchers working in the fields of complex systems, statistical physics, computational intelligence, and biological physics.

Computational Ecology

Computational Ecology PDF

Author: Wenjun Zhang

Publisher: World Scientific

Published: 2010

Total Pages: 310

ISBN-13: 9814282634

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Ch. 1. Introduction. 1. Computational ecology. 2. Artificial neural networks and ecological applications -- pt. I. Artificial neural networks : principles, theories and algorithms. ch. 2. Feedforward neural networks. 1. Linear separability and perceptron. 2. Some analogies of multilayer feedforward networks. 3. Functionability of multilayer feedforward networks. ch. 3. Linear neural networks. 1. Linear neural networks. 2. LMS rule. ch. 4. Radial basis function neural networks. 1. Theory of RBF neural network. 2. Regularized RBF neural network. 3. RBF neural network learning. 4. Probabilistic neural network. 5. Generalized regression neural network. 6. Functional link neural network. 7. Wavelet neural network. ch. 5. BP neural network. 1. BP algorithm. 2. BP theorem. 3. BP training. 4. Limitations and improvements of BP algorithm. ch. 6. Self-organizing neural networks. 1. Self-organizing feature map neural network. 2. Self-organizing competitive learning neural network. 3. Hamming neural network. 4. WTA neural network. 5. LVQ neural network. 6. Adaptive resonance theory. ch. 7. Feedback neural networks. 1. Elman neural network. 2. Hopfield neural networks. 3. Simulated annealing. 4. Boltzmann machine. ch. 8. Design and customization of artificial neural networks. 1. Mixture of experts. 2. Hierarchical mixture of experts. 3. Neural network controller. 4. Customization of neural networks. ch. 9. Learning theory, architecture choice and interpretability of neural networks. 1. Learning theory. 2. Architecture choice. 3. Interpretability of neural networks. ch. 10. Mathematical foundations of artificial neural networks. 1. Bayesian methods. 2. Randomization, bootstrap and Monte Carlo techniques. 3. Stochastic process and stochastic differential equation. 4. Interpolation. 5. Function approximation. 6. Optimization methods. 7. Manifold and differential geometry. 8. Functional analysis. 9. Algebraic topology. 10. Motion stability. 11. Entropy of a system. 12. Distance or similarity measures. ch. 11. Matlab neural network toolkit. 1. Functions of perceptron. 2. Functions of linear neural networks. 3. Functions of BP neural network. 4. Functions of self-organizing neural networks. 5. Functions of radial basis neural networks. 6. Functions of probabilistic neural network. 7. Function of generalized regression neural network. 8. Functions of Hopfield neural network. 9. Function of Elman neural network -- pt. II. Applications of artificial neural networks in ecology. ch. 12. Dynamic modeling of survival process. 1. Model description. 2. Data description. 3. Results. 4. Discussion. ch. 13. Simulation of plant growth process. 1. Model description. 2. Data source. 3. Results. 4. Discussion. ch. 14. Simulation of food intake dynamics. 1. Model description. 2. Data description. 3. Results. 4. Discussion. ch. 15. Species richness estimation and sampling data documentation. 1. Estimation of plant species richness on grassland. 2. Documentation of sampling data of invertebrates. ch. 16. Modeling arthropod abundance from plant composition of grassland community. 1. Model description. 2. Data description. 3. Results. 4. Discussion. ch. 17. Pattern recognition and classification of ecosystems and functional groups. 1. Model description. 2. Data source. 3. Results. 4. Discussion. ch. 18. Modeling spatial distribution of arthropods. 1. Model description. 2. Data description. 3. Results. 4. Discussion. ch. 19. Risk assessment of species invasion and establishment. 1. Invasion risk assessment based on species assemblages. 2. Determination of abiotic factors influencing species invasion. ch. 20. Prediction of surface ozone. 1. BP prediction of daily total ozone. 2. MLP Prediction of hourly ozone levels. ch. 21. Modeling dispersion and distribution of oxide and nitrate pollutants. 1. Modeling nitrogen dioxide dispersion. 2. Simulation of nitrate distribution in ground water. ch. 22. Modeling terrestrial biomass. 1. Estimation of aboveground grassland biomass. 2. Estimation of trout biomass

Future Sustainable Ecosystems

Future Sustainable Ecosystems PDF

Author: Nathaniel K Newlands

Publisher: CRC Press

Published: 2016-10-03

Total Pages: 290

ISBN-13: 131535666X

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Future Sustainable Ecosystems: Complexity, Risk, Uncertainty provides an interdisciplinary, integrative overview of environmental problem-solving using statistics. It shows how statistics can be used to solve diverse environmental and socio-economic problems involving food, water, energy scarcity, and climate change risks. It synthesizes interdisciplinary theory, concepts, definitions, models and findings involved in complex global sustainability problem-solving, making it an essential guide and reference. It includes real-world examples and applications making the book accessible to a broader interdisciplinary readership. Discussions include a broad, integrated perspective on sustainability, integrated risk, multi-scale changes and impacts taking place within ecosystems worldwide. State-of-the-art statistical techniques, including Bayesian hierarchical, spatio-temporal, agent-based and game-theoretic approaches are explored. The author then focuses on the real-world integration of observational and experimental data and its use within statistical models.

Frontiers in Ecology, Evolution and Complexity

Frontiers in Ecology, Evolution and Complexity PDF

Author: Mariana Benítez

Publisher: CopIt ArXives

Published: 2014-07-08

Total Pages: 283

ISBN-13: 1938128052

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Advances in molecular biology, remote sensing, systems biology, bioinformatics, non-linear science, the physics of complex systems and other fields have rendered a great amount of data that remain to be integrated into models and theories that are capable of accounting for the complexity of ecological systems and the evolutionary dynamics of life. It is thus necessary to provide a solid basis to discuss and reflect on these and other challenges both at the local and global scales. This volume aims to delineate an integrative and interdisciplinary view that suggests new avenues in research and teaching, critically discusses the scope of the diverse methods in the study of complex systems, and points at key open questions. Finally, this book will provide students and specialists with a collection of high quality open access essays that will contribute to integrate Ecology, Evolution and Complexity in the context of basic research and in the field of Sustainability Sciences.