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Information Physics—Towards a New Conception of Physical Reality

The concept of information plays a fundamental role in our everyday experience, but is conspicuously absent in framework of classical physics. Over the last century, quantum theory and a series of other developments in physics and related subjects have brought the concept of information and the interface between an agent and the physical world into increasing prominence. As a result, over the last few decades, there has arisen a growing belief amongst many physicists that the concept of information may have a critical role to play in our understanding of the workings of the physical world, both in more deeply understanding existing physical theories and in formulating of new theories. In this paper, I describe the origin of the informational view of physics, illustrate some of the work inspired by this view, and give some indication of its implications for the development of a new conception of physical reality.

 

Information Physics—Towards a New Conception of Physical Reality
Philip Goyal

Information 2012, 3(4), 567-594; http://dx.doi.org/10.3390/info3040567


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Complex Systems General Interest
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Information Physics—Towards a New Conception of Physical Reality

The concept of information plays a fundamental role in our everyday experience, but is conspicuously absent in framework of classical physics. Over the last century, quantum theory and a series of other developments in physics and related subjects have brought the concept of information and the interface between an agent and the physical world into increasing prominence. As a result, over the last few decades, there has arisen a growing belief amongst many physicists that the concept of information may have a critical role to play in our understanding of the workings of the physical world, both in more deeply understanding existing physical theories and in formulating of new theories. In this paper, I describe the origin of the informational view of physics, illustrate some of the work inspired by this view, and give some indication of its implications for the development of a new conception of physical reality.

 

Information Physics—Towards a New Conception of Physical Reality
Philip Goyal

Information 2012, 3(4), 567-594; http://dx.doi.org/10.3390/info3040567


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Smart cities of the future

Smart cities of the future | Complex Systems General Interest | Scoop.it

Here we sketch the rudiments of what constitutes a smart city which we define as a city in which ICT is merged with traditional infrastructures, coordinated and integrated using new digital technologies. We first sketch our vision defining seven goals which concern: developing a new understanding of urban problems; effective and feasible ways to coordinate urban technologies; models and methods for using urban data across spatial and temporal scales; developing new technologies for communication and dissemination; developing new forms of urban governance and organisation; defining critical problems relating to cities, transport, and energy; and identifying risk, uncertainty, and hazards in the smart city. To this, we add six research challenges: to relate the infrastructure of smart cities to their operational functioning and planning through management, control and optimisation; to explore the notion of the city as a laboratory for innovation; to provide portfolios of urban simulation which inform future designs; to develop technologies that ensure equity, fairness and realise a better quality of city life; to develop technologies that ensure informed participation and create shared knowledge for democratic city governance; and to ensure greater and more effective mobility and access to opportunities for urban populations.

Smart cities of the future
M. Batty, K. W. Axhausen, F. Giannotti, A. Pozdnoukhov, A. Bazzani, M. Wachowicz, G. Ouzounis, Y. Portugali
The European Physical Journal Special Topics
November 2012, Volume 214, Issue 1, pp 481-518
http://dx.doi.org/10.1140/epjst/e2012-01703-3


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luiy's curator insight, April 8, 2013 5:45 AM

We begin by defining the state of the art, explaining the science of smart cities. We define six scenarios based on new cities badging themselves as smart, older cities regenerating themselves as smart, the development of science parks, tech cities, and technopoles focused on high technologies, the development of urban services using contemporary ICT, the use of ICT to develop new urban intelligence functions, and the development of online and mobile forms of participation. Seven project areas are then proposed: Integrated Databases for the Smart City, Sensing, Networking and the Impact of New Social Media, Modelling Network Performance, Mobility and Travel Behaviour, Modelling Urban Land Use, Transport and Economic Interactions, Modelling Urban Transactional Activities in Labour and Housing Markets, Decision Support as Urban Intelligence, Participatory Governance and Planning Structures for the Smart City. Finally we anticipate the paradigm shifts that will occur in this research and define a series of key demonstrators which we believe are important to progressing a science of smart cities.

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New Rules for the New Economy

New Rules for the New Economy | Complex Systems General Interest | Scoop.it

1) Embrace the Swarm. As power flows away from the center, the competitive advantage belongs to those who learn how to embrace decentralized points of control.

2) Increasing Returns. As the number of connections between people and things add up, the consequences of those connections multiply out even faster, so that initial successes aren't self-limiting, but self-feeding.

3) Plentitude, Not Scarcity. As manufacturing techniques perfect the art of making copies plentiful, value is carried by abundance, rather than scarcity, inverting traditional business propositions.

4) Follow the Free. As resource scarcity gives way to abundance, generosity begets wealth. Following the free rehearses the inevitable fall of prices, and takes advantage of the only true scarcity: human attention.

5) Feed the Web First. As networks entangle all commerce, a firm's primary focus shifts from maximizing the firm's value to maximizing the network's value. Unless the net survives, the firm perishes.

6) Let Go at the Top. As innovation accelerates, abandoning the highly successful in order to escape from its eventual obsolescence becomes the most difficult and yet most essential task.

7) From Places to Spaces. As physical proximity (place) is replaced by multiple interactions with anything, anytime, anywhere (space), the opportunities for intermediaries, middlemen, and mid-size niches expand greatly.

8) No Harmony, All Flux. As turbulence and instability become the norm in business, the most effective survival stance is a constant but highly selective disruption that we call innovation.

9) Relationship Tech. As the soft trumps the hard, the most powerful technologies are those that enhance, amplify, extend, augment, distill, recall, expand, and develop soft relationships of all types.

10) Opportunities Before Efficiencies. As fortunes are made by training machines to be ever more efficient, there is yet far greater wealth to be had by unleashing the inefficient discovery and creation of new opportunities.


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Xaos's curator insight, December 19, 2012 12:24 AM

1) Embrace the Swarm. As power flows away from the center, the competitive advantage belongs to those who learn how to embrace decentralized points of control.

2) Increasing Returns. As the number of connections between people and things add up, the consequences of those connections multiply out even faster, so that initial successes aren't self-limiting, but self-feeding.

3) Plentitude, Not Scarcity. As manufacturing techniques perfect the art of making copies plentiful, value is carried by abundance, rather than scarcity, inverting traditional business propositions.

4) Follow the Free. As resource scarcity gives way to abundance, generosity begets wealth. Following the free rehearses the inevitable fall of prices, and takes advantage of the only true scarcity: human attention.

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Financial price dynamics and pedestrian counterflows: A comparison of statistical stylized facts

Financial price dynamics and pedestrian counterflows: A comparison of statistical stylized facts | Complex Systems General Interest | Scoop.it

Financial price dynamics and pedestrian counterflows: A comparison of statistical stylized facts

Daniel R. Parisi, Didier Sornette, and Dirk Helbing

Accepted Friday Dec 14, 2012

We propose and document the evidence for an analogy between the dynamics of granular counter-flows in the presence of bottlenecks or restrictions and financial price formation processes. Using extensive simulations, we find that the counter-flows of simulated pedestrians through a door display eight stylized facts observed in financial markets when the density around the door is compared with the logarithm of the price. Finding so many stylized facts is very rare indeed among all agent-based models of financial markets. The stylized properties are present already when the agents in the pedestrian model are assumed to display a zero-intelligent behavior. If agents are given decision-making capacity and adapt to partially follow the majority, periods of herding behavior may additionally occur. This generates the very slow decay of the autocorrelation of absolute return due to an intermittent dynamics. Our finding suggest that the stylized facts in the fluctuations of the financial prices result from a competition of two groups with opposite interests in the presence of a constraint funneling the flow of transactions to a narrow band of prices with limited liquidity.


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Getting interaction theory (IT) together: Integrating developmental, phenomenological, enactive, and dynamical approaches to social interaction

We argue that progress in our scientific understanding of the ‘social mind’ is hampered by a number of unfounded assumptions. We single out the widely shared assumption that social behavior depends solely on the capacities of an individual agent. In contrast, both developmental and phenomenological studies suggest that the personal-level capacity for detached ‘social cognition’ (conceived as a process of theorizing about and/or simulating another mind) is a secondary achievement that is dependent on more immediate processes of embodied social interaction. We draw on the enactive approach to cognitive science to further clarify this strong notion of ‘social interaction’ in theoretical terms. In addition, we indicate how this interaction theory (IT) could eventually be formalized with the help of a dynamical systems perspective on the interaction process, especially by making use of evolutionary robotics modeling. We conclude that bringing together the methods and insights of developmental, phenomenological, enactive and dynamical approaches to social interaction can provide a promising framework for future research. Keywords: theory of mind; cognitive science; phenomenology; embodied cognition; dynamical systems theory; enactive approach; social cognition; interaction theory; evolutionary robotics

 

Getting interaction theory (IT) together

Integrating developmental, phenomenological, enactive, and dynamical approaches to social interaction

Tom Froese, Shaun Gallagher

Interaction Studies 13:3. 2012. iii, 164 pp. (pp. 436–468)

http://benjamins.com/#catalog/journals/is.13.3.06fro/details


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Self-organized criticality in neural network models

It has long been argued that neural networks have to establish and maintain a certain intermediate level of activity in order to keep away from the regimes of chaos and silence. Strong evidence for criticality has been observed in terms of spatio-temporal activity avalanches first in cultures of rat cortex by Beggs and Plenz (2003) and subsequently in many more experimental setups. These findings sparked intense research on theoretical models for criticality and avalanche dynamics in neural networks, where usually some dynamical order parameter is fed back onto the network topology by adapting the synaptic couplings. We here give an overview of existing theoretical models of dynamical networks. While most models emphasize biological and neurophysiological detail, our path here is different: we pick up the thread of an early self-organized critical neural network model by Bornholdt and Roehl (2001) and test its applicability in the light of experimental data. Keeping the simplicity of early models, and at the same time lifting the drawback of a spin formulation with respect to the biological system, we here study an improved model (Rybarsch and Bornholdt, 2012b) and show that it adapts to criticality exhibiting avalanche statistics that compare well with experimental data without the need for parameter tuning.

Self-organized criticality in neural network models
Matthias Rybarsch, Stefan Bornholdt
http://arxiv.org/abs/1212.3106


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Truthy: Enabling the Study of Online Social Networks

The broad adoption of online social networking platforms has made it possible to study communication networks at an unprecedented scale. Digital trace data can be compiled into large data sets of online discourse. However, it is a challenge to collect, store, filter, and analyze large amounts of data, even by experts in the computational sciences. Here we describe our recent extensions to Truthy, a system that collects Twitter data to analyze discourse in near real-time. We introduce several interactive visualizations and analytical tools with the goal of enabling citizens, journalists, and researchers to understand and study online social networks at multiple scales.

 

Truthy: Enabling the Study of Online Social Networks

Karissa McKelvey, Fil Menczer

http://arxiv.org/abs/1212.4565


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Bankruptcy cascades in interbank markets: Gabriele Tedeschi, Amin Mazloumian, Mauro Gallegati, Dirk Helbing

Bankruptcy cascades in interbank markets: Gabriele Tedeschi, Amin Mazloumian, Mauro Gallegati, Dirk Helbing | Complex Systems General Interest | Scoop.it

We study a credit network and, in particular, an interbank system with an agent-based model. To understand the relationship between business cycles and cascades of bankruptcies, we model a three-sector economy with goods, credit and interbank market. In the interbank market, the participating banks share the risk of bad debits, which may potentially spread a bank’s liquidity problems through the network of banks. Our agent-based model sheds light on the correlation between bankruptcy cascades and the endogenous economic cycle of booms and recessions. It also demonstrates the serious trade-off between, on the one hand, reducing risks of individual banks by sharing them and, on the other hand, creating systemic risks through credit-related interlinkages of banks. As a result of our study, the dynamics underlying the meltdown of financial markets in 2008 becomes much better understandable.


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