Information, Complexity, Computation
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Information, Complexity, Computation
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Social Relationships and the Emergence of Social Networks

In complex social systems such as those of many mammals, including humans, groups (and hence ego-centric social networks) are commonly structured in discrete layers. We describe a computational model for the development of social relationships based on agents' strategies for social interaction that favour more less-intense, or fewer more-intense partners. A trust-related process controls the formation and decay of relationships as a function of interaction frequency, the history of interaction, and the agents' strategies. A good fit of the observed layers of human social networks was found across a range of model parameter settings. Social interaction strategies which favour interacting with existing strong ties or a time-variant strategy produced more observation-conformant results than strategies favouring more weak relationships. Strong-tie strategies spread in populations under a range of fitness conditions favouring wellbeing, whereas weak-tie strategies spread when fitness favours foraging for food. The implications for modelling the emergence of social relationships in complex structured social networks are discussed.

 

Alistair Sutcliffe, Di Wang and Robin Dunbar (2012)

Social Relationships and the Emergence of Social Networks

Journal of Artificial Societies and Social Simulation 15 (4) 3
http://jasss.soc.surrey.ac.uk/15/4/3.html


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On the necessity of complexity

Wolfram's Principle of Computational Equivalence (PCE) implies that universal complexity abounds in nature. This paper comprises three sections. In the first section we consider the question why there are so many universal phenomena around. So, in a sense, we week a driving force behind the PCE if any. We postulate a principle GNS that we call the Generalized Natural Selection Principle that together with the Church-Turing Thesis is seen to be equivalent to a weak version of PCE. In the second section we ask the question why we do not observe any phenomena that are complex but not-universal. We choose a cognitive setting to embark on this question and make some analogies with formal logic. In the third and final section we report on a case study where we see rich structures arise everywhere.

 

On the necessity of complexity

Joost J. Joosten

http://arxiv.org/abs/1211.1878


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The Local Information Dynamics of Distributed Computation in Complex Systems

The Local Information Dynamics of Distributed Computation in Complex Systems | Information, Complexity, Computation | Scoop.it

The nature of distributed computation in complex systems has often been described in terms of memory, communication and processing. This thesis presents a complete information-theoretic framework to quantify these operations on information (i.e. information storage, transfer and modification), and in particular their dynamics in space and time. The framework is applied to cellular automata, and delivers important insights into the fundamental nature of distributed computation and the dynamics of complex systems (e.g. that gliders are dominant information transfer agents). Applications to several important network models, including random Boolean networks, suggest that the capability for information storage and coherent transfer are maximised near the critical regime in certain order-chaos phase transitions. Further applications to study and design information structure in the contexts of computational neuroscience and guided self-organisation underline the practical utility of the techniques presented here.

 

 

"The Local Information Dynamics of Distributed Computation in Complex Systems"

Joseph T. Lizier

(With foreword by Dr. Mikhail Prokopenko)

Springer Theses, Springer: Berlin/Heidelberg, 2013.

http://dx.doi.org/10.1007/978-3-642-32952-4

 


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VI International Workshop on Nature Inspired Cooperative Strategies for Optimization NICSO 2013

VI International Workshop on Nature Inspired Cooperative Strategies for Optimization, September 2 - 4, 2013, Canterbury, UK...

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Complexity Perspectives on Language, Communication and Society

Complexity Perspectives on Language, Communication and Society | Information, Complexity, Computation | Scoop.it

The “language-communication-society” triangle defies traditional scientific approaches. Rather, it is a phenomenon that calls for an integration of complex, transdisciplinary perspectives, if we are to make any progress in understanding how it works. The highly diverse agents in play are not merely cognitive and/or cultural, but also emotional and behavioural in their specificity. Indeed, the effort may require building a theoretical and methodological body of knowledge that can effectively convey the characteristic properties of phenomena in human terms.

New complexity approaches allow us to rethink our limited and mechanistic images of human societies and create more appropriate emo-cognitive dynamic and holistic models. We have to enter into dialogue with the complexity views coming out of other more ‘material’ sciences, but we also need to take steps in the linguistic and psycho-sociological fields towards creating perspectives and concepts better fitted to human characteristics.

Our understanding of complexity is different – but not opposed – to the one that is more commonly found in texts written by people working in physics or computer science, for example. The goal of this book is to extend the knowledge of these other more ‘human’ or socially oriented perspectives on complexity, taking account of the language and communication singularities of human agents in society.

 

Complexity Perspectives on Language, Communication and Society
Series: Understanding Complex Systems
Massip-Bonet, Àngels; Bastardas-Boada, Albert (Eds.)


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Civilisation is making humanity less intelligent, study claims - Telegraph

Civilisation is making humanity less intelligent, study claims - Telegraph | Information, Complexity, Computation | Scoop.it
The simplicity of modern life is making us more stupid, according to a scientific theory which claims humanity may have reached its intellectual and emotional peak as early as 4,000 BC.
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Noam Chomsky on Where Artificial Intelligence Went Wrong

Noam Chomsky on Where Artificial Intelligence Went Wrong | Information, Complexity, Computation | Scoop.it

Long but interesting interview with linguist Noam Chomsky fom the Atlantic, on A.I. Wether you agree or disagree with his views on computation and intigence and the directions taken by AI community and nueirscience - it makes for a stimulating read. Click on the image or the title to learn more.


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Global Civil Unrest: Contagion, Self-Organization, and Prediction

Civil unrest is a powerful form of collective human dynamics, which has led to major transitions of societies in modern history. The study of collective human dynamics, including collective aggression, has been the focus of much discussion in the context of modeling and identification of universal patterns of behavior. In contrast, the possibility that civil unrest activities, across countries and over long time periods, are governed by universal mechanisms has not been explored. Here, records of civil unrest of 170 countries during the period 1919–2008 are analyzed. It is demonstrated that the distributions of the number of unrest events per year are robustly reproduced by a nonlinear, spatially extended dynamical model, which reflects the spread of civil disorder between geographic regions connected through social and communication networks. The results also expose the similarity between global social instability and the dynamics of natural hazards and epidemics.

 

Braha D (2012) Global Civil Unrest: Contagion, Self-Organization, and Prediction. PLoS ONE 7(10): e48596. http://dx.doi.org/10.1371/journal.pone.0048596


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Vida 14 Art & Artificial Life International Competition

Over the last decade, in the same formal space, VIDA has been bringing together inter-disciplinary projects that respond to new development in Artificial Live. By means of formal strategies that defy the boundaries between existing practices, these projects offer new ways of reflecting on what we understand by life.

Fundacion Telefonica announces the Vida 14.0 Art & Artificial Life International Competition, which for the last fourteen years has awarded prizes for artistic projects using technological mediums offering innovative approaches to research into artificial life.

The projects may be based on systems which emulate, imitate or speculate on the notion of life through current research and technology. These systems may involve attributes of agency and autonomy which display specific behaviour, are dynamic, react to their surroundings and evolve, and which question the frontiers between what is alive and what is not, between synthetic and organic life.


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Complex Adaptive Systems Modeling - a SpringerOpen journal

Complex Adaptive Systems Modeling  - a SpringerOpen journal | Information, Complexity, Computation | Scoop.it

Complex Adaptive Systems Modeling (CASM) is a highly multidisciplinary modeling and simulation journal that serves as a unique forum for original, high-quality peer-reviewed papers with a specific interest and scope limited to agent-based and complex network-based modeling paradigms for Complex Adaptive Systems (CAS).


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The Emergence of Organizations and Market

The Emergence of Organizations and Markets

~ Walter W. Powell (author) More about this product
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The social sciences have sophisticated models of choice and equilibrium but little understanding of the emergence of novelty. Where do new alternatives, new organizational forms, and new types of people come from? Combining biochemical insights about the origin of life with innovative and historically oriented social network analyses, John Padgett and Walter Powell develop a theory about the emergence of organizational, market, and biographical novelty from the coevolution of multiple social networks. They demonstrate that novelty arises from spillovers across intertwined networks in different domains. In the short run actors make relations, but in the long run relations make actors.

This theory of novelty emerging from intersecting production and biographical flows is developed through formal deductive modeling and through a wide range of original historical case studies. Padgett and Powell build on the biochemical concept of autocatalysis--the chemical definition of life--and then extend this autocatalytic reasoning to social processes of production and communication. Padgett and Powell, along with other colleagues, analyze a very wide range of cases of emergence. They look at the emergence of organizational novelty in early capitalism and state formation; they examine the transformation of communism; and they analyze with detailed network data contemporary science-based capitalism: the biotechnology industry, regional high-tech clusters, and the open source community.

 

The Emergence of Organizations and Markets
John F. Padgett, Walter W. Powell

Princeton University Press (October 14, 2012)


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Slime mold uses an externalized spatial “memory” to navigate in complex environments

Spatial memory enhances an organism’s navigational ability. Memory typically resides within the brain, but what if an organism has no brain? We show that the brainless slime mold Physarum polycephalum constructs a form of spatial memory by avoiding areas it has previously explored. This mechanism allows the slime mold to solve the U-shaped trap problem—a classic test of autonomous navigational ability commonly used in robotics—requiring the slime mold to reach a chemoattractive goal behind a U-shaped barrier.

 

Slime mold uses an externalized spatial “memory” to navigate in complex environments
Chris R. Reid, Tanya Latty, Audrey Dussutour, and Madeleine Beekman

PNAS October 8, 2012

http://dx.doi.org/10.1073/pnas.1215037109


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Imperfect Alternatives and the Invisible Elephant: The Complex Nature of Environmental Governance

Environmental governance decisions, like other public policies, are often based upon the assumption that having the ‘correct’ legal principles is the key to describing and prescribing the law. Yet, one of the most inescapable and persistent issues in law is its very concept. Western civil law and common law scholars have sought to understand where, how and in what form law emerges. How do normative orders form legal orders, or juridicities?

Moreover, law is not only founded on legal principles but also set within a wider social, economic, cultural as well as environmental context. As interdisciplinary approaches to the study of law expand, disciplines such as the sociology of law and legal anthropology have exposed how dogmatic principles can often be incongruent with the legal reality or law in practice. Instead alternative normative orders seem to emerge, each being complex and imperfect. By contrast, the economic analysis of law generally has sought to view normative behavior through the narrower lens of market exchange in which an ‘invisible hand’ simply guides ‘rational’ agents to the optimal solution. In recent years much has been learned from nonlinear dynamics and complex adaptive systems about how complex and imperfect [normative] behaviors can emerge from simple rules (Miller and Page 2007). The approach taken here unites these seemingly contradictory perspectives in order to portray the emergence of self-organizing governance alternatives. The article proposes a means to structure a multidisciplinary analysis of Corsican governance to better understand the underlining decision-making process and frame the corresponding forces that form legal orders.

 

Imperfect Alternatives and the Invisible Elephant: The Complex Nature of Environmental Governance

Jovita De Loatch

http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2153128


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On the necessity of complexity

Wolfram's Principle of Computational Equivalence (PCE) implies that universal complexity abounds in nature. This paper comprises three sections. In the first section we consider the question why there are so many universal phenomena around. So, in a sense, we week a driving force behind the PCE if any. We postulate a principle GNS that we call the Generalized Natural Selection Principle that together with the Church-Turing Thesis is seen to be equivalent to a weak version of PCE. In the second section we ask the question why we do not observe any phenomena that are complex but not-universal. We choose a cognitive setting to embark on this question and make some analogies with formal logic. In the third and final section we report on a case study where we see rich structures arise everywhere.

 

On the necessity of complexity

Joost J. Joosten

http://arxiv.org/abs/1211.1878


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How Computational Models Predict the Behavior of Complex Systems

In this paper, we argue for the centrality of prediction in the use of computational models in science. We focus on the consequences of the irreversibility of computational models and on the conditional or ceteris paribus, nature of the kinds of their predictions. By irreversibility, we mean the fact that computational models can generally arrive at the same state via many possible sequences of previous states. Thus, while in the natural world, it is generally assumed that physical states have a unique history, representations of those states in a computational model will usually be compatible with more than one possible history in the model. We describe some of the challenges involved in prediction and retrodiction in computational models while arguing that prediction is an essential feature of non-arbitrary decision making. Furthermore, we contend that the non-predictive virtues of computational models are dependent to a significant degree on the predictive success of the models in question.

 

How Computational Models Predict the Behavior of Complex Systems
John Symons and Fabio Boschetti

FOUNDATIONS OF SCIENCE
2012, http://dx.doi.org/10.1007/s10699-012-9307-6


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Cognitive Agent-based Computing-I

Cognitive Agent-based Computing-I | Information, Complexity, Computation | Scoop.it

Complex Systems are made up of numerous interacting sub-components. Non-linear interactions of these components or agents give rise to emergent behavior observable at the global scale. Agent-based modeling
and simulation is a proven paradigm which has previously been used for effective computational modeling of complex systems in various domains. Because of its popular use across different scientific domains, research in agent-based modeling has primarily been
vertical in nature.
The goal of this book is to provide a single hands-on guide to developing cognitive agent-based models for the exploration of emergence across various types of complex systems. We present practical ideas and
examples for researchers and practitioners for the building of agent-based models using a horizontal approach - applications are demonstrated in a number of exciting domains as diverse as wireless sensors networks, peer-to-peer networks, complex social systems,
research networks and epidemiological HIV.

 

Cognitive Agent-based Computing-I

A Unified Framework for Modeling Complex Adaptive Systems using Agent-based & Complex Network-based Methods
Series: SpringerBriefs in Cognitive Computation
Niazi, Muaz A, Hussain, Amir


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Global Civil Unrest: Contagion, Self-Organization, and Prediction

Global Civil Unrest: Contagion, Self-Organization, and Prediction | Information, Complexity, Computation | Scoop.it

Civil unrest is a powerful form of collective human dynamics, which has led to major transitions of societies in modern history. The study of collective human dynamics, including collective aggression, has been the focus of much discussion in the context of modeling and identification of universal patterns of behavior. In contrast, the possibility that civil unrest activities, across countries and over long time periods, are governed by universal mechanisms has not been explored. Here, records of civil unrest of 170 countries during the period 1919–2008 are analyzed. It is demonstrated that the distributions of the number of unrest events per year are robustly reproduced by a nonlinear, spatially extended dynamical model, which reflects the spread of civil disorder between geographic regions connected through social and communication networks. The results also expose the similarity between global social instability and the dynamics of natural hazards and epidemics.

 

Braha D (2012) Global Civil Unrest: Contagion, Self-Organization, and Prediction. PLoS ONE 7(10): e48596. http://dx.doi.org/10.1371/journal.pone.0048596


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The Biological Origin of Linguistic Diversity

In contrast with animal communication systems, diversity is characteristic of almost every aspect of human language. Languages variously employ tones, clicks, or manual signs to signal differences in meaning; some languages lack the noun-verb distinction (e.g., Straits Salish), whereas others have a proliferation of fine-grained syntactic categories (e.g., Tzeltal); and some languages do without morphology (e.g., Mandarin), while others pack a whole sentence into a single word (e.g., Cayuga). A challenge for evolutionary biology is to reconcile the diversity of languages with the high degree of biological uniformity of their speakers. Here, we model processes of language change and geographical dispersion and find a consistent pressure for flexible learning, irrespective of the language being spoken. This pressure arises because flexible learners can best cope with the observed high rates of linguistic change associated with divergent cultural evolution following human migration. Thus, rather than genetic adaptations for specific aspects of language, such as recursion, the coevolution of genes and fast-changing linguistic structure provides the biological basis for linguistic diversity. Only biological adaptations for flexible learning combined with cultural evolution can explain how each child has the potential to learn any human language.

 

Baronchelli A, Chater N, Pastor-Satorras R, Christiansen MH (2012) The Biological Origin of Linguistic Diversity. PLoS ONE 7(10): e48029. http://dx.doi.org/10.1371/journal.pone.0048029


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IoT Takes Off Bottom-Up

IoT Takes Off Bottom-Up | Information, Complexity, Computation | Scoop.it
To see the power of the the Internet of Things, with its capability of linking high quality sensors cheaply and interactively, you don't have to wait for the big supplier companies and traditional business to show the way forward....
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Announcing the Santa Fe Institute’s Massive Open On-Line Courses | Santa Fe Institute

Announcing the Santa Fe Institute’s Massive Open On-Line Courses | Santa Fe Institute | Information, Complexity, Computation | Scoop.it

Santa Fe Institute will be launching a series of MOOCs (Massive Open On-line Courses), covering the field of complex systems science. Our first course, Introduction to Complexity, will be an accessible introduction to the field, with no pre-requisites. You don't need a science or math background to take this introductory course; it simply requires an interest in the field and the willingness to participate in a hands-on approach to the subject.
In this ten-week course, you'll learn about the tools used by complex systems scientists to understand, and sometimes to control, complex systems. The topics you'll learn about include dynamics, chaos, fractals, information theory, computation theory, evolution and adaptation, agent-based modeling, and networks. You’ll also get a sense of how these topics fit together to help explain how complexity arises and evolves in nature, society, and technology.
Introduction to Complexity will be free and open to anyone. The instructor is Melanie Mitchell, External Professor at SFI, Professor of Computer Science at Portland State University, and author of the award-winning book, Complexity: A Guided Tour. The course will begin in early 2013.
To receive e-mail updates about how to register for this course, please visit http://www.santafe.edu/mooc/subscribe

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Will we ever… reveal all the secrets of life from DNA?

Will we ever… reveal all the secrets of life from DNA? | Information, Complexity, Computation | Scoop.it

Good article on the BBC Future website : As our technologies and understanding advance, will we eventually be able to look at a pile of raw DNA sequence and glean all the workings of the organism it belongs to? Just as physicists can use the laws of mechanics to predict the motion of an object, can biologists use fundamental ideas in genetics and molecular biology to predict the traits and flaws of a body based solely on its genes? Could we pop a genome into a black box, and print out the image of a human? Or a fly? Or a mouse?

Not easily... Click on the image or the title to learn more.


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The City as an Ecosystem

The City as an Ecosystem | Information, Complexity, Computation | Scoop.it

Cities cannot be meaningfully recognized by their parts – they function as whole – and their character is emergent being co-authored by its communities. Cities are being robbed of their relationship to people and reduced into modular, meaningless items.

 

The City as an Ecosystem
Rachel Armstrong

http://hplusmagazine.com/2012/06/13/the-city-as-an-ecosystem/


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SourceForge.net: PyCX Project: PyCX 0.2 now available

SourceForge.net: PyCX Project: PyCX 0.2 now available | Information, Complexity, Computation | Scoop.it
The PyCX Project aims to develop an online repository of simple, crude, yet easy-to-understand Python sample codes for dynamic complex systems simulations, including iterative maps, cellular automata, dynamical networks and agent-based models.
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Reaction-Diffusion Automata: Phenomenology, Localisations, Computation

Reaction-Diffusion Automata: Phenomenology, Localisations, Computation | Information, Complexity, Computation | Scoop.it

Reaction-diffusion and excitable media are amongst most intriguing substrates. Despite apparent simplicity of the physical processes involved the media exhibit a wide range of amazing patterns: from target and spiral waves to travelling localisations and stationary breathing patterns. These media are at the heart of most natural processes, including morphogenesis of living beings, geological
formations, nervous and muscular activity, and socio-economic developments. This book explores a minimalist paradigm of studying reaction-diffusion and excitable media using locally-connected networks of finite-state machines: cellular automata and automata on proximity graphs. Cellular automata are marvellous objects per se because they show us how to generate and manage complexity using very simple rules of dynamical transitions. When combined with the reaction-diffusion paradigm the cellular automata become an essential user-friendly tool for modelling natural systems and designing future and emergent computing architectures. The book brings together hot topics
of non-linear sciences, complexity, and future and emergent computing. It shows how to discover propagating localisation and perform computation with them in very simple two-dimensional automaton models. Paradigms, models and implementations presented in the book strengthen the theoretical foundations in the area for future and emergent computing and lay key stones towards
physical embodied information processing systems.

Reaction-Diffusion Automata:
Phenomenology, Localisations, Computation

by Andrew Adamatzky

http://www.springer.com/physics/complexity/book/978-3-642-31077-5

 

 


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Natural networks as thermodynamic systems

Natural networks are considered as thermodynamic systems that evolve from one state to another by consuming free energy. The least-time consumption of free energy is found to result in ubiquitous scale-free characteristics. The network evolution will yield the scale-independent qualities because the least-time imperative will prefer attachment of nodes that contribute most to the free-energy consumption. The analysis of evolutionary equation of motion, derived from statistical physics of open systems, reveals that evolution of natural networks is a path-dependent and nondeterministic process. Despite the noncomputability of evolution, many mathematical models of networks can be recognized as approximations of the least-time process as well as many measures of networks can be appreciated as practical assessments of the system's thermodynamic status.

 

Natural networks as thermodynamic systems

Tuomo Hartonen1, Arto Annila1,2,3,*
Complexity

http://dx.doi.org/10.1002/cplx.21428

 


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