Most scientists will characterize complexity as the result of one or more factors out of three: (i) high dimensionality, (ii) interaction networks, and (iii) nonlinearity. High dimensionality alone need not give rise to complexity. The best known cases come from linear algebra: To determine the eigenvalues and eigenvectors of a large quadratic matrix, for example, is complicated but not complex. Every mathematician, physicist or economist, and most scholars from other disciplines can write down an algorithm that would work provided infinite resources in computer time and storage space are given. (...)
How complexity originates: Examples from history reveal additional roots to complexity Peter Schuster Complexity DOI: 10.1002/cplx.21841
“Flocking” or “swarming” behavior is omnipresent in the living world, observed in birds, fish, and even bacteria. Strikingly similar collective action can also be seen in biomolecules within and between cells.
The question What is Complexity? has occupied a great deal of time and paper over the last 20 or so years. There are a myriad different perspectives and definitions but still no consensus. In this paper I take a phenomenological approach, identifying several factors that discriminate well between systems that would be consensually agreed to be simple versus others that would be consensually agreed to be complex - biological systems and human languages. I argue that a crucial component is that of structural building block hierarchies that, in the case of complex systems, correspond also to a functional hierarchy. I argue that complexity is an emergent property of this structural/functional hierarchy, induced by a property - fitness in the case of biological systems and meaning in the case of languages - that links the elements of this hierarchy across multiple scales. Additionally, I argue that non-complex systems "are" while complex systems "do" so that the latter, in distinction to physical systems, must be described not only in a space of states but also in a space of update rules (strategies) which we do not know how to specify. Further, the existence of structural/functional building block hierarchies allows for the functional specialisation of structural modules as amply observed in nature. Finally, we argue that there is at least one measuring apparatus capable of measuring complexity as characterised in the paper - the human brain itself.
The New England Complex Systems Institute has funding for postdoctoral and predoctoral research appointments. We look for outstanding applicants with training in physics, mathematics or computer science. We value strong writing abilities. Candidates should be interested in contributing to a wide range of NECSI's research areas, including analysis and modeling of
Socio-economic systems relevant to: - The food and economic crises, - Conflicts, revolutions, and ethnic violence - International development, and - Pandemics
All systems in nature have one thing in common: they process information. Information is registered in the state of a system and its elements, implicitly and invisibly. As elements interact, information is transferred and modified. Indeed, bits of information about the state of one element will travel—imperfectly—to the state of the other element, forming its new state. This storage, transfer, and modification of information, possibly between levels of a multi level system, is imperfect due to randomness or noise. From this viewpoint, a system can be formalized as a collection of bits that is organized according to its rules of dynamics and its topology of interactions. Mapping out exactly how these bits of information percolate through the system could reveal new fundamental insights in how the parts orchestrate to produce the properties of the system. A theory of information processing would be capable of defining a set of universal properties of dynamical multi level complex systems, which describe and compare the dynamics of diverse complex systems ranging from social interaction to brain networks, from financial markets to biomedicine. Each possible combination of rules of dynamics and topology of interactions, with disparate semantics, would reduce to a single language of information processing.
Guest Editor: Dr. Rick Quax
Deadline for manuscript submissions: 28 February 2015
The interdisciplinary approach to problems that till recently were addressed in the hermetic framework of distinct disciplines such as physics, informatics, biology or sociology constitutes today one of the most active and innovative areas of...
Quantum Teleportation and Entanglement: A Hybrid Approach to Optical Quantum Information Processing Offer Price $97.72 ISBN:3527409300 Authors Akira Furusawa, Peter van Loock List Price : $140.00 Availablity Usually ships in 24 hours Publisher :...
The Conference on Complex Systems (CCS) has become a major venue for the Complex Systems Community since they were started in 2003. After a successful event in the USA in 2015 we are now back in Europe. In AMSTERDAM(!). CCS’16 will be a major international conference and event in the area of complex systems and interdisciplinary science in general.
Contemporary complexity theory has been instrumental in providing novel rigorous definitions for some classic philosophical concepts, including emergence. In an attempt to provide an account of emergence that is consistent with complexity and dynamical systems theory, several authors have turned to the notion of constraints on state transitions. Drawing on complexity theory directly, this paper builds on those accounts, further developing the constraint-based interpretation of emergence and arguing that such accounts recover many of the features of more traditional accounts. We show that the constraint-based account of emergence also leads naturally into a meaningful definition of self-organization, another concept that has received increasing attention recently. Along the way, we distinguish between order and organization, two concepts which are frequently conflated. Finally, we consider possibilities for future research in the philosophy of complex systems, as well as applications of the distinctions made in this paper.
Self-Organization, Emergence, and Constraint in Complex Natural Systems Jonathan Lawhead
Funding is available for applicants interested in carrying out fundamental and applied research in the field of complex systems. The research will involve theoretical work as well as computer simulations. It will aim to discover fundamental connections between information-theoretic and statistical-mechanical approaches to self-organisation, while investigating a variety of topics in nonlinear critical phenomena, with particular focus on information dynamics during phase transitions.
The PhD will be supervised by Prof. Mikhail Prokopenko. The applicant will join the Complex Systems Research Group (CSRG) at The School of Civil Engineering – The University of Sydney. The CSRG group comprises ten academics, and has wide collaborations across the University, Australia, and internationally. It is a vibrant, world-leading group in the fields of guided self-organisation and critical phenomena forecasting.
The scholarship also includes covering the fees payable by international students.
In recent years, ideas such as "life is information processing" or "information holds the key to understanding life" have become more common. However, how can information, or more formally Information Theory, increase our understanding of life, or life-like systems?
Information Theory not only has a profound mathematical basis, but also typically provides an intuitive understanding of processes, such as learning, behavior and evolution terms of information processing.
In this special issue, we are interested in both: a.) the information-theoretic formalization and quantification of different aspects of life, such as driving forces of learning and behavior generation, information flows between neurons, swarm members and social agents, and information theoretic aspects of evolution and adaptation and b.) the simulation and creation of life-like systems with previously identified principles and incentives.
Topics with relation to artificial and natural systems:
information theoretic intrinsic motivationsinformation theoretic quantification of behaviorinformation theoretic guidance of artificial evolutioninformation theoretic guidance of self-organizationinformation theoretic driving forces behind learninginformation theoretic driving forces behind behaviorinformation theory in swarmsinformation theory in social behaviorinformation theory in evolutioninformation theory in the braininformation theory in system-environment distinctioninformation theory in the perception action loopinformation theoretic definitions of life
Dr. Christoph Salge Dr. Georg Martius Dr. Keyan Ghazi-Zahedi Dr. Daniel Polani Guest Editors
Deadline for manuscript submissions: 28 February 2015
The school will take place from 29 June to 3 July 2015 The scope of the school is to present recent advances in complex systems discussing applications of statistical mechanics of non-equilibrium and disordered systems, theories of complex networks and other stochastic systems to different topics in materials science, social sciences, biology and biomedical research. The broad choice of interdisciplinary topics is designed to expose the students to some of the multiple facets of complex systems theory. The school is open to graduate students and postdoctoral fellows working in complex systems and related fields.
Advances in Complex Systems Lake Como School of Advanced Studies, 29 June – 3 July 2015 (Como)
Climate Change May Impact El Nino Rainfall Patterns reportingclimatescience.com Chadwick, R., Boutle, I. & Martin, G. Spatial Patterns of Precipitation Change in CMIP5: Why the Rich Do Not Get Richer in the Tropics.
Numerical Heat Transfer and Fluid Flow (Hemisphere Series on Computational Methods in Mechanics and Thermal Science) Offer Price $196.23 ISBN:0891165223 Authors Suhas Patankar List Price : $231.00 Availablity Usually ships in 24 hours Publisher :...
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