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Are You Ready to Lose Control? - strategy+business (blog)

Are You Ready to Lose Control? - strategy+business (blog) | Complex Systems and X-Events | Scoop.it
Are You Ready to Lose Control?
strategy+business (blog)
But in today's knowledge economy, where enterprises are complex, adaptive systems, it's counterproductive. The real problem is confusion between control and order.
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X Center Network – Mathematical Model for the Dynamic Behavior of the Demographic Transition by Roger D. Jones

X Center Network – Mathematical Model for the Dynamic Behavior of the Demographic Transition by Roger D. Jones | Complex Systems and X-Events | Scoop.it
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Urban Resilience & regional resilience and behavior by Mr.Brudermann - YouTube

Thomas Bruderman Assistant Professor - Institute for Systems Science, Innovation & Sustainability Research (ISIS), Austria Speaker at the X-Network Conferenc...
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Tina Seelig: The 6 Characteristics of Truly Creative People | 99u

Tina Seelig: The 6 Characteristics of Truly Creative People | 99u | Complex Systems and X-Events | Scoop.it
In this compelling 99U talk, Stanford professor Tina Seelig shows us how the top organizations in the world foster a creative environment.

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Erika Harrison's curator insight, December 27, 2013 5:23 PM

“Often, answers are baked into the questions we ask. We need to question, examine, and reframe the questions we’re asking.”

 

About this presentation

Determined not to just write just another book on creativity, Stanford professor Tina Seelig painstakingly researched what makes good ideas spring forward. The result is her “innovation engine,” a special mix of six characteristics like attitude, resources and environment.

 

But the special concoction of forces that makes our ideas come to life is nothing with out the willingness to fail. “Most call it failure, but we scientists just call it data,” she says. The most creative organizations and people embrace experimentation to get the needed data to determine they’re on to something. 

 

“Workers are puzzle builders, they get stuck when missing a piece,” she says. Truly creative people “are quilt makers — they can fit anything together.”

 

About Tina Seelig

Tina Seelig is the executive director for the Stanford Technology Ventures Program and the director of the National Center for Engineering Pathways to Innovation (Epicenter) at Stanford University’s School of Engineering. She teaches courses on creativity, innovation, and entrepreneurship in the department of Management Science and Engineering, and within the Hasso Plattner Institute of Design at Stanford. She received the 2009 Gordon Prize from the National Academy of Engineering, recognizing her as a national leader in engineering education.

 

Seelig earned her PhD in 1985 from Stanford University School of Medicine, where she studied Neuroscience. She has been a management consultant, multimedia producer, and an entrepreneur. Seelig has also written 16 popular science books and educational games. Her newest books are Wish I Knew When I Was 20 (HarperCollins 2009) and inGenius: A Crash Course on Creativity(HarperCollins 2012).

Emeric Nectoux's curator insight, December 29, 2013 1:56 AM

A must watch! Great inspiring presentation on how to innovate. 

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The Creative Climate

The Creative Climate | Complex Systems and X-Events | Scoop.it
Creative tension between people and within individuals is fundamental to social evolution.

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Erika Harrison's curator insight, July 21, 4:40 PM

"the Lennon-McCartney story also illustrates the key feature of creativity; it is the joining of the unlike to create harmony. Creativity rarely flows out of an act of complete originality. It is rarely a virgin birth. It is usually the clash of two value systems or traditions, which, in collision, create a transcendent third thing".

Keith Hamon's curator insight, July 22, 8:12 AM

OpEd about the dialogical tension that creates creativity.

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The Power of Networks | World Economic Forum 2012

The Power of Networks | World Economic Forum 2012 | Complex Systems and X-Events | Scoop.it
The World Economic Forum (WEF) is a Geneva-based non-profit organization best known for its Annual Meeting in Davos, Switzerland, the Annual Meeting of New Champions in China (Summer Davos) and the Summit on the Global Agenda in Dubai.

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Erika Harrison's curator insight, August 9, 2013 1:43 PM

"*Nowadays, any organization should employ network scientists/analysts who are able to map and analyse complex systems that are of importance to the organization (e.g. the organization itself, its activities, a country’s economic activities, transportation networks, research networks).

 

*Interconnectivity is beneficial but also brings in vulnerability: if you and I are connected we can share resources; meanwhile your problems can become mine and vice versa.

 

*The concept of “crystallized imagination” refers to things that are first in our head and then become reality. This concept can be turned into network applied research on economic complexity of a country’s economic activities and development prospects".

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Information Entropy-Based Metrics for Measuring Emergences in Artificial Societies

Emergence is a common phenomenon, and it is also a general and important concept in complex dynamic systems like artificial societies. Usually, artificial societies are used for assisting in resolving several complex social issues (e.g., emergency management, intelligent transportation system) with the aid of computer science. The levels of an emergence may have an effect on decisions making, and the occurrence and degree of an emergence are generally perceived by human observers. However, due to the ambiguity and inaccuracy of human observers, to propose a quantitative method to measure emergences in artificial societies is a meaningful and challenging task. This article mainly concentrates upon three kinds of emergences in artificial societies, including emergence of attribution, emergence of behavior, and emergence of structure. Based on information entropy, three metrics have been proposed to measure emergences in a quantitative way. Meanwhile, the correctness of these metrics has been verified through three case studies (the spread of an infectious influenza, a dynamic microblog network, and a flock of birds) with several experimental simulations on the Netlogo platform. These experimental results confirm that these metrics increase with the rising degree of emergences. In addition, this article also has discussed the limitations and extended applications of these metrics.

 

Information Entropy-Based Metrics for Measuring Emergences in Artificial Societies
Mingsheng Tang  and Xinjun Mao

Entropy 2014, 16, 4583-4602; http://dx.doi.org/10.3390/e16084583


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JIDT: An information-theoretic toolkit for studying the dynamics of complex systems

Complex systems are increasingly being viewed as distributed information processing systems, particularly in the domains of computational neuroscience, bioinformatics and Artificial Life. This trend has resulted in a strong uptake in the use of (Shannon) information-theoretic measures to analyse the dynamics of complex systems in these fields. We introduce the Java Information Dynamics Toolkit (JIDT): a Google code project which provides a standalone, (GNU GPL v3 licensed) open-source code implementation for empirical estimation of information-theoretic measures from time-series data. While the toolkit provides classic information-theoretic measures (e.g. entropy, mutual information, conditional mutual information), it ultimately focusses on implementing higher-level measures for information dynamics. That is, JIDT focusses on quantifying information storage, transfer and modification, and the dynamics of these operations in space and time. For this purpose, it includes implementations of the transfer entropy and active information storage, their multivariate extensions and local or pointwise variants. JIDT provides implementations for both discrete and continuous-valued data for each measure, including various types of estimator for continuous data (e.g. Gaussian, box-kernel and Kraskov-Stoegbauer-Grassberger) which can be swapped at run-time due to Java's object-oriented polymorphism. Furthermore, while written in Java, the toolkit can be used directly in MATLAB, GNU Octave and Python. We present the principles behind the code design, and provide several examples to guide users

 

"JIDT: An information-theoretic toolkit for studying the dynamics of complex systems"
Joseph T. Lizier, arXiv:1408.3270, 2014
http://arxiv.org/abs/1408.3270


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Eli Levine's curator insight, August 19, 11:11 AM

This could be useful.

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Columbia University and the Van Alen Institute Map How Our Brains Navigate the City

Columbia University and the Van Alen Institute Map How Our Brains Navigate the City | Complex Systems and X-Events | Scoop.it
The GSAPP’s Cloud Lab teams up with neurologists and the design institute to track how urban environments can make people relaxed or tense.

This spring, the Cloud Lab at Columbia University and the Van Alen Institute tackled the challenge of assessing and mapping how people respond to their environment as a part of Van Alen’s Elsewhere series on wellness in the city.

Instead of the typical focus groups, however, the researchers tracked brainwaves to gauge the mental activities of nearly 100 volunteers; using electroencephalography-based (EEG) measurements and the GPS tracking app, the research team collected more than 1 gigabyte of data over 200 walking sessions that, in theory, create a snapshot of a day-in-the-life of the neighborhood’s mental states. 

Presenting the data in a manner that retained its spatial qualities required the researchers to develop their own software for visualization. At a public follow-up presentation in May, the team presented the simplified data on a 3D map of DUMBO. Areas in cyan indicate places in which participants were in a more meditative and relaxed state, while areas in red indicate places where participants had a more focused or heightened sense of awareness...


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Blue Urbanism: Exploring Connections Between Cities and Oceans (by Timothy Beatley)

Blue Urbanism: Exploring Connections Between Cities and Oceans

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What would it mean to live in cities designed to foster feelings of connectedness to the ocean? As coastal cities begin planning for climate change and rising sea levels, author Timothy Beatley sees opportunities for rethinking the relationship between urban development and the ocean. Modern society is more dependent upon ocean resources than people are commonly aware of—from oil and gas extraction to wind energy, to the vast amounts of fish harvested globally, to medicinal compounds derived from sea creatures, and more. In Blue Urbanism, Beatley argues that, given all we’ve gained from the sea, city policies, plans, and daily urban life should acknowledge and support a healthy ocean environment.

The book explores issues ranging from urban design and land use, to resource extraction and renewable energy, to educating urbanites about the wonders of marine life. Beatley looks at how emerging practices like “community supported fisheries” and aquaponics can provide a sustainable alternative to industrial fishing practices. Other chapters delve into incentives for increasing use of wind and tidal energy as renewable options to oil and gas extraction that damages ocean life, and how the shipping industry is becoming more “green.” Additionally, urban citizens, he explains, have many opportunities to interact meaningfully with the ocean, from beach cleanups to helping scientists gather data.

While no one city “has it all figured out,” Beatley finds evidence of a changing ethic in cities around the world: a marine biodiversity census in Singapore, decreasing support for shark-finning in Hong Kong, “water plazas” in Rotterdam, a new protected area along the rocky shore of Wellington, New Zealand, “bluebelt” planning in Staten Island, and more. Ultimately he explains we must create a culture of “ocean literacy” using a variety of approaches, from building design and art installations that draw inspiration from marine forms, to encouraging citizen volunteerism related to oceans, to city-sponsored research, and support for new laws that protect marine health.

 

 


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Self-organization in complex systems as decision making

The idea is advanced that self-organization in complex systems can be treated as decision making (as it is performed by humans) and, vice versa, decision making is nothing but a kind of self-organization in the decision maker nervous systems. A mathematical formulation is suggested based on the definition of probabilities of system states, whose particular cases characterize the probabilities of structures, patterns, scenarios, or prospects. In this general framework, it is shown that the mathematical structures of self-organization and of decision making are identical. This makes it clear how self-organization can be seen as an endogenous decision making process and, reciprocally, decision making occurs via an endogenous self-organization. The approach is illustrated by phase transitions in large statistical systems, crossovers in small statistical systems, evolutions and revolutions in social and biological systems, structural self-organization in dynamical systems, and by the probabilistic formulation of classical and behavioral decision theories. In all these cases, self-organization is described as the process of evaluating the probabilities of macroscopic states or prospects in the search for a state with the largest probability. The general way of deriving the probability measure for classical systems is the principle of minimal information, that is, the conditional entropy maximization under given constraints. Behavioral biases of decision makers can be characterized in the same way as analogous to quantum fluctuations in natural systems

 

Self-organization in complex systems as decision making
V.I. Yukalov, D. Sornette
arXiv:1408.1529, 2014
http://arxiv.org/abs/1408.1529


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Eli Levine's curator insight, August 16, 1:28 PM

Basically, the process of decision-making is apart of the system as a whole and not an externality. Where is the clear distinction between a user and the computer program that they choose to run? Can't it all be viewed as one thing? 

 

Amazing implications for governing and government relative to society. 

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Robustness and Evolvability of the Human Signaling Network

Biological systems are known to be robust and evolvable to internal mutations and external environmental changes. What causes these apparently contradictory properties? This study shows that the human signaling network can be decomposed into two structurally distinct subgroups of links that provide both evolvability to environmental changes and robustness against internal mutations. The decomposition of the human signaling network reveals an evolutionary design principle of the network, and also facilitates the identification of potential drug targets.

 

Kim J, Vandamme D, Kim J-R, Munoz AG, Kolch W, et al. (2014) Robustness and Evolvability of the Human Signaling Network. PLoS Comput Biol 10(7): e1003763. http://dx.doi.org/10.1371/journal.pcbi.1003763


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Artificial Life and the Web: WebAL Comes of Age

A brief survey is presented of the first 18 years of web-based Artificial Life ("WebAL") research and applications, covering the period 1995-2013. The survey is followed by a short discussion of common methodologies employed and current technologies relevant to WebAL research. The paper concludes with a quick look at what the future may hold for work in this exciting area.

 

Artificial Life and the Web: WebAL Comes of Age
Tim Taylor

http://arxiv.org/abs/1407.5719


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How A Simple Spambot Became The Second Most Powerful Member Of An Italian Social Network

How A Simple Spambot Became The Second Most Powerful Member Of An Italian Social Network | Complex Systems and X-Events | Scoop.it
The surprising story of how an experiment to automate the creation of popularity and influence became successful beyond all expectation.

 

Sometimes fascinating discoveries are made entirely by accident. This is a good example. A few years ago, Luca Maria Aiello and a few pals from the University of Turin in Italy began studying a social network called aNobii.com in which people exchange information and opinions about the books they love. Each person has a site that anybody can visit. Users can then choose to set up social links with others.

 

To map out the structure of the network, Aiello and co created an automated crawler that starts by visiting one person’s profile on the network and then all of the people that connect to this node in turn. It then visits each of the people that link to these nodes and so on. In this way, the bot builds up a map of the network.

 

Crucially, to gain access to the network, the team had to create an empty user account for their crawler which they called lajello.

The team let the lajello crawler loose in September 2009. At this time the network was small enough for lajello to map out the entire structure once every 15 days or so.

 

Then in July 2010, aNobii.com changed its default user settings so that every user could see all the others that had visited their personal site. “As a result, our crawler left a trace of its passage in all the profiles reached approximatively twice a month,” say Aiello and co.


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Rogers 14'01'' - YouTube

14 Minutes from X-Center Network April 23-25, 2014 Annual Conference Vienna Austria _Speaker Roger Jones_Topic Population explosion
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APPROACHING X-EVENT IN THE FOREST INDUSTRY by Wilenius Markku 19'19'' - YouTube

X Center Network Annual conference 2014 in Vienna Topic: APPROACHING X-EVENT IN THE FOREST INDUSTRY
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Robert Wright: The logic of non-zero-sum progress

"Author Robert Wright explains "non-zero-sumness," a game-theory term describing how players with linked fortunes tend to cooperate for mutual benefit. This dynamic has guided our biological and cultural evolution, he says -- but our unwillingness to understand one another, as in the clash between the Muslim world and the West, will lead to all of us losing the "game." Once we recognize that life is a non-zero-sum game, in which we all must cooperate to succeed, it will force us to see that moral progress -- a move toward empathy -- is our only hope".


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Puppies! Now that I’ve got your attention, complexity theory | Nicholas Perony | TEDxZurich

Puppies! Now that I’ve got your attention, complexity theory | Nicholas Perony | TEDxZurich | Complex Systems and X-Events | Scoop.it
Animal behavior isn't complicated, but it is complex. Nicolas Perony studies how individual animals -- be they Scottish Terriers, bats or meerkats -- follow simple rules that, collectively, create larger patterns of behavior. And how this complexity born of simplicity can help them adapt to new circumstances, as they arise.

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Systems Thinking and the Future of Cities

Systems Thinking and the Future of Cities | Complex Systems and X-Events | Scoop.it
The idea that nothing exists in isolation−but only as part of a system−has long been embedded in folklore, religious scriptures, and common sense.

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Erika Harrison's curator insight, August 15, 7:49 PM

In Brief

The idea that nothing exists in isolation−but only as part of a system−has long been embedded in folklore, religious scriptures, and common sense. Yet, systems dynamics as a science has yet to transform the way we conduct the public business. This article first briefly explores the question of why advances in systems theory have failed to transform public policy. The second part describes the ways in which our understanding of systems is growing−not so much from theorizing, but from practical applications in agriculture, building design, and medical science. The third part focuses on whether and how that knowledge and systems science can be deployed to improve urban governance in the face of rapid climate destabilization so that sustainability becomes the norm, not the occasional success story.


Key Concepts

Reducing wholes to parts lies at the core of the scientific worldview we inherited from Galileo, Bacon, Descartes, and their modern acolytes in the sciences of economics, efficiency, and management.The decades between 1950 and 1980 were the grand era for systems theory. However despite a great deal of talk about systems, we continue to administer, organize, analyze, manage, and govern complex ecological systems as if they were a collection of isolated parts and not an indissoluble union of energy, water, soils, land, forests, biota, and air.Much of what we have learned about managing real systems began in agriculture. One of the most important lessons being that land is an evolving organism of interrelated parts soils, hydrology, biota, wildlife, plants, animals, and people.The challenge is to transition organized urban complexity built on an industrial model and designed for automobiles, sprawl, and economic growth into coherent, civil, and durable places.A systems perspective to urban governance is a lens by which we might see more clearly through the fog of change, and potentially better manage the complex cause and effect relationships between social and ecological phenomena. The application of systems offers at least six possibilities to improve urban governance.

 

A system is an interconnected set of elements that is coherently organized in a way that achieves something . . . . [it] must consist of three kinds of things: elements, interconnections, and a function or purpose.
—Donella Meadows, Thinking in Systems1

 

A system [is] (a) a set of units or elements interconnected so that changes in some elements or their relations produce changes in other parts of the system, and (b) the entire system exhibits properties and behaviors that are different from those of the parts.
—Robert Jervis, Systems Effects 2

 

One of the most important ideas in modern science is the idea of a system; and it is almost impossible to define.
—Garrett Hardin, The Cybernetics of Competition3

Tobias Beckwith's curator insight, August 16, 1:45 PM

One of the things that gives real wizards their "powers," is the ability to see the world as systems within systems within systems... and then finding the leverage points, where a small action in one part of the system might cause a very large response elsewhere...

 

This post and article discuss that whole idea in a bit more depth. I found it to be a good read.

Gary Bamford's curator insight, August 20, 2:08 AM

Non-linear futures.

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Programmable self-assembly in a thousand-robot swarm

Self-assembly enables nature to build complex forms, from multicellular organisms to complex animal structures such as flocks of birds, through the interaction of vast numbers of limited and unreliable individuals. Creating this ability in engineered systems poses challenges in the design of both algorithms and physical systems that can operate at such scales. We report a system that demonstrates programmable self-assembly of complex two-dimensional shapes with a thousand-robot swarm. This was enabled by creating autonomous robots designed to operate in large groups and to cooperate through local interactions and by developing a collective algorithm for shape formation that is highly robust to the variability and error characteristic of large-scale decentralized systems. This work advances the aim of creating artificial swarms with the capabilities of natural ones.

 

Programmable self-assembly in a thousand-robot swarm
Michael Rubenstein, Alejandro Cornejo, Radhika Nagpal

Science 15 August 2014:
Vol. 345 no. 6198 pp. 795-799
http://dx.doi.org/10.1126/science.1254295


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Eli Levine's curator insight, August 16, 1:31 PM

Imagine what we can do as a society with this way of thinking and feeling in our governing bodies. This isn't social engineering, but the submission to discovered, natural law in the society, environment, economy, and universe as a whole.

 

It's all one thing. 

 

Enjoy. 

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Graphing New Yorkers' Lives Through the Open Data Portal

Graphing New Yorkers' Lives Through the Open Data Portal | Complex Systems and X-Events | Scoop.it
The I Quant NY blog mines NYC's massive data clearinghouse to visualize issues facing city dwellers, from education to eating.

Ben Wellington is the man behind I Quant NY, a blog dedicated to telling the stories hidden in New York City’s Open Data Portal, a clearinghouse of more than 1,300 data sets from city agencies. Started by the city government in 2011, the open data initiative’s goal is to facilitate government transparency and increase civic engagement.

The blog itself comes out of a stats course Wellington teaches at Pratt Institute’s graduate program for city and regional planning, where he uses these data sets in coursework. Covering everything from gender divides in Citi Bike usage to finding the farthest point away from a Starbucks in Manhattan, Wellington’s larger mission is to get people thinking critically about the numbers that, if analyzed right, can be the key to understanding New York City.

He spoke to CityLab about his blog, his hope for the open data movement, and some of his favorite data sets.


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40 Maps That Explain The Internet

40 Maps That Explain The Internet | Complex Systems and X-Events | Scoop.it

The internet increasingly pervades our lives, delivering information to us no matter where we are. It takes a complex system of cables, servers, towers, and other infrastructure, developed over decades, to allow us to stay in touch with our friends and family so effortlessly. Here are 40 maps that will help you better understand the internet — where it came from, how it works, and how it's used by people around the world.


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Villubicae's curator insight, August 19, 8:43 AM
Interestant OF course and for any reasons
Javier Antonio Bellina's curator insight, August 19, 9:38 AM

Cuarenta Mapas que explican Internet.

Edgar Mata's curator insight, August 21, 11:50 PM

Here are 40 maps that will help you better understand the internet

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Social Dynamics (by Brian Skyrms)

Social Dynamics

~ Brian Skyrms (author) More about this product
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Brian Skyrms presents eighteen essays which apply adaptive dynamics (of cultural evolution and individual learning) to social theory. Altruism, spite, fairness, trust, division of labor, and signaling are treated from this perspective. Correlation is seen to be of fundamental importance. Interactions with neighbors in space, on static networks, and on co-evolving dynamics networks are investigated. Spontaneous emergence of social structure and of signaling systems are examined in the context of learning dynamics.

 

 


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Limits on fundamental limits to computation

An indispensable part of our personal and working lives, computing has also become essential to industries and governments. Steady improvements in computer hardware have been supported by periodic doubling of transistor densities in integrated circuits over the past fifty years. Such Moore scaling now requires ever-increasing efforts, stimulating research in alternative hardware and stirring controversy. To help evaluate emerging technologies and increase our understanding of integrated-circuit scaling, here I review fundamental limits to computation in the areas of manufacturing, energy, physical space, design and verification effort, and algorithms. To outline what is achievable in principle and in practice, I recapitulate how some limits were circumvented, and compare loose and tight limits. Engineering difficulties encountered by emerging technologies may indicate yet unknown limits.

 

Limits on fundamental limits to computation
Igor L. Markov
Nature 512, 147–154 (14 August 2014) http://dx.doi.org/10.1038/nature13570


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ComplexInsight's curator insight, August 15, 2:31 AM

Discussion of limits is key to creating new ideas - Igor Markov's paper is worth reading for exploring lmitations and engineering implications and to trigger off new discussions and ideas. Worth reading.

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Collective Learning and Optimal Consensus Decisions in Social Animal Groups

Learning has been studied extensively in the context of isolated individuals. However, many organisms are social and consequently make decisions both individually and as part of a collective. Reaching consensus necessarily means that a single option is chosen by the group, even when there are dissenting opinions. This decision-making process decouples the otherwise direct relationship between animals' preferences and their experiences (the outcomes of decisions). Instead, because an individual's learned preferences influence what others experience, and therefore learn about, collective decisions couple the learning processes between social organisms. This introduces a new, and previously unexplored, dynamical relationship between preference, action, experience and learning. Here we model collective learning within animal groups that make consensus decisions. We reveal how learning as part of a collective results in behavior that is fundamentally different from that learned in isolation, allowing grouping organisms to spontaneously (and indirectly) detect correlations between group members' observations of environmental cues, adjust strategy as a function of changing group size (even if that group size is not known to the individual), and achieve a decision accuracy that is very close to that which is provably optimal, regardless of environmental contingencies. Because these properties make minimal cognitive demands on individuals, collective learning, and the capabilities it affords, may be widespread among group-living organisms. Our work emphasizes the importance and need for theoretical and experimental work that considers the mechanism and consequences of learning in a social context.

 

Kao AB, Miller N, Torney C, Hartnett A, Couzin ID (2014) Collective Learning and Optimal Consensus Decisions in Social Animal Groups. PLoS Comput Biol 10(8): e1003762. http://dx.doi.org/10.1371/journal.pcbi.1003762


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Programmable self-assembly in a thousand-robot swarm

Self-assembly enables nature to build complex forms, from multicellular organisms to complex animal structures such as flocks of birds, through the interaction of vast numbers of limited and unreliable individuals. Creating this ability in engineered systems poses challenges in the design of both algorithms and physical systems that can operate at such scales. We report a system that demonstrates programmable self-assembly of complex two-dimensional shapes with a thousand-robot swarm. This was enabled by creating autonomous robots designed to operate in large groups and to cooperate through local interactions and by developing a collective algorithm for shape formation that is highly robust to the variability and error characteristic of large-scale decentralized systems. This work advances the aim of creating artificial swarms with the capabilities of natural ones.

 

Programmable self-assembly in a thousand-robot swarm
Michael Rubenstein, Alejandro Cornejo, Radhika Nagpal

Science 15 August 2014:
Vol. 345 no. 6198 pp. 795-799
http://dx.doi.org/10.1126/science.1254295


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Eli Levine's curator insight, August 16, 1:31 PM

Imagine what we can do as a society with this way of thinking and feeling in our governing bodies. This isn't social engineering, but the submission to discovered, natural law in the society, environment, economy, and universe as a whole.

 

It's all one thing. 

 

Enjoy.