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New Rules for the New Economy

New Rules for the New Economy | Papers | 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.


Via Xaos, Spaceweaver, ddrrnt
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Xaos's curator insight, December 19, 2012 3:24 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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Participatory Science and Computing for Our Complex World

Participatory Science and Computing for Our Complex World | Papers | Scoop.it
The European Physical Journal Special Topics
Volume 214, Issue 1, November 2012
Participatory Science and Computing for Our Complex World
http://link.springer.com/journal/11734/214/1/page/1
Complexity Digest's insight:

This special issue includes contributions from members of the FuturICT Flagship Proposal

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Computer engineering: Feeling the heat

Computer engineering: Feeling the heat | Papers | Scoop.it
A laptop computer can double as an effective portable knee-warmer — pleasant in a cold office. But a bigger desktop machine needs a fan. A data centre as large as those used by Google needs a high-volume flow of cooling water. And with cutting-edge supercomputers, the trick is to keep them from melting. A world-class machine at the Leibniz Supercomputing Centre in Munich, for example, operates at 3 petaflops (3 × 1015 operations per second), and the heat it produces warms some of the centre's buildings. Current trends suggest that the next milestone in computing — an exaflop machine performing at 1018 flops — would consume hundreds of megawatts of power (equivalent to the output of a small nuclear plant) and turn virtually all of that energy into heat.
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Smart cities of the future

Smart cities of the future | Papers | 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 8:45 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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Individual memory and the emergence of cooperation

Individual memory and the emergence of cooperation | Papers | Scoop.it
The social brain hypothesis states that selection pressures associated with complex social relationships have driven the evolution of sophisticated cognitive processes in primates. We investigated how the size of cooperative primate communities depends on the memory of each of its members and on the pressure exerted by natural selection. To this end we devised an evolutionary game theoretical model in which social interactions are modelled in terms of a repeated Prisoner's Dilemma played by individuals who may exhibit a different memory capacity. Here, memory is greatly simplified and mapped onto a single parameter m describing the number of conspecifics whose previous action each individual can remember. We show that increasing m enables cooperation to emerge and be maintained in groups of increasing sizes. Furthermore, harsher social dilemmas lead to the need for a higher m in order to ensure high levels of cooperation. Finally, we show how the interplay between the dilemma individuals face and their memory capacity m allows us to define a critical group size below which cooperation may thrive, and how this value depends sensitively on the strength of natural selection.

Individual memory and the emergence of cooperation
João Moreira, Jeromos Vukov, Cláudia Sousa, Francisco C. Santos, André F. d'Almeida, Marta D. Santos, Jorge M. Pacheco
Animal Behaviour
Available online 4 December 2012
In Press, Corrected Proof
http://dx.doi.org/10.1016/j.anbehav.2012.10.030
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Interdependency and hierarchy of exact epidemic models on networks

Over the years numerous models of SIS (susceptible - infected - susceptible) disease dynamics unfolding on networks have been proposed. Here, we discuss the links between many of these models and how they can be viewed as more general motif-based models. We illustrate how the different models can be derived from one another and, where this is not possible, discuss extensions to established models that enables this derivation. We also derive a general result for the exact differential equations for the expected number of an arbitrary motif directly from the Kolmogorov/master equations and conclude with a comparison of the performance of the different closed systems of equations on networks of varying structure.

Interdependency and hierarchy of exact epidemic models on networks
Timothy J Taylor, Istvan Z Kiss
http://arxiv.org/abs/1212.3124
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Three paradoxes of leadership

Three paradoxes of leadership | Papers | Scoop.it
Executives must come to grips with three paradoxes of leadership. First, an organization changes more easily when it doesn’t try to change everything. Second, it’s more likely to succeed if it both controls and empowers its employees. Finally, it should accept the variability and failure that accompany innovation. Much as circus performers spin plates to keep them in the air, executives must control the “spinning plates” these three paradoxes create.
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Assortativity decreases the robustness of interdependent networks

It was recently recognized that interdependencies among different networks can play a crucial role in triggering cascading failures and, hence, systemwide disasters. A recent model shows how pairs of interdependent networks can exhibit an abrupt percolation transition as failures accumulate. We report on the effects of topology on failure propagation for a model system consisting of two interdependent networks. We find that the internal node correlations in each of the two interdependent networks significantly changes the critical density of failures that triggers the total disruption of the two-network system. Specifically, we find that the assortativity (i.e., the likelihood of nodes with similar degree to be connected) within a single network decreases the robustness of the entire system. The results of this study on the influence of assortativity may provide insights into ways of improving the robustness of network architecture and, thus, enhance the level of protection of critical infrastructures.

 

Di Zhou, H. Eugene Stanley, Gregorio D’Agostino and Antonio Scala

"Assortativity decreases the robustness of interdependent networks"

Phys. Rev. E 86, 066103 (2012)

http://link.aps.org/doi/10.1103/PhysRevE.86.066103

 

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Link creation and information spreading over social and communication ties in an interest-based online social network

Complex dynamics of social media emerge from the interaction between the patterns of social connectivity of users and the information exchanged along such social ties. Unveiling the underlying mechanisms that drive the evolution of online social systems requires a deep understanding of the interplay between these two aspects. Based on the case of the aNobii social network, an online service for book readers, we investigate the dynamics of link creation and the social influence phenomenon that may trigger information diffusion in the social graph. By confirming that social partner selection is strongly driven by structural, geographical, and topical proximity, we develop a machine-learning social link recommender for individual users trained on a set of features selected as best predictive out of several and we test it on the still widely unexplored domain of a network of interest.

 

Link creation and information spreading over social and communication ties in an interest-based online social network
Luca M Aiello, Alain Barrat, Ciro Cattuto, Rossano Schifanella and Giancarlo Ruffo

EPJ Data Science 2012, 1:12 http://dx.doi.org/10.1140/epjds12

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The science of cities: Life in the concrete jungle

The science of cities: Life in the concrete jungle | Papers | Scoop.it

(...) the growing field of urban ecology, in which scientists study cities as if they were ecosystems. In the past, artificial and natural elements have been studied separately, but urban ecologists seek to understand the interplay between them — such as how heat and high carbon dioxide levels boost plant growth, how trees cool cities and how green spaces improve animal habitat.

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Adapting to a warmer world: No going back

Adapting to a warmer world: No going back | Papers | Scoop.it

Just a decade ago, 'adaptation' was something of a dirty word in the climate arena — an insinuation that nations could continue with business as usual and deal with the mess later. But greenhouse-gas emissions are increasing at an unprecedented rate and countries have failed to negotiate a successor to the Kyoto Protocol climate treaty. That stark reality has forced climate researchers and policy-makers to explore ways to weather some of the inevitable changes.

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Contesting the “Nature” Of Conformity: What Milgram and Zimbardo's Studies Really Show

Understanding of the psychology of tyranny is dominated by classic studies from the 1960s and 1970s: Milgram's research on obedience to authority and Zimbardo's Stanford Prison Experiment. Supporting popular notions of the banality of evil, this research has been taken to show that people conform passively and unthinkingly to both the instructions and the roles that authorities provide, however malevolent these may be. Recently, though, this consensus has been challenged by empirical work informed by social identity theorizing. This suggests that individuals' willingness to follow authorities is conditional on identification with the authority in question and an associated belief that the authority is right.

 

Haslam SA, Reicher SD (2012) Contesting the “Nature” Of Conformity: What Milgram and Zimbardo's Studies Really Show. PLoS Biol 10(11): e1001426. http://dx.doi.org/10.1371/journal.pbio.1001426

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The Origins of Scaling in Cities

Cities are perhaps the ultimate expression of human sociality displaying at once humanity’s greatest achievements and some of its most difficult challenges. Despite the increasing importance of cities in human societies our ability to understand them scientifically, and manage them in practice, has remained unsatisfactorily limited. The greatest difficulties to any scientific approach to cities have resulted from their many interdependent facets, as social, economic, infrastructural and spatial complex systems, which exist in similar but changing forms over a huge range of scales. Here, I show how cities may evolve following a small set of basic principles that operate locally and can explain how cities change gradually from the bottom-up. As a result I obtain a theoretical framework that derives the general open-ended properties of cities through the optimization of a set of local conditions. This framework is used to predict, in a unified and quantitative way, the average social, spatial and infrastructural properties of cities as a set of scaling relations that apply to all urban systems, many of which have been observed in nations around the world. Finally, I compare and contrast the structure and dynamics of cities to those of other complex systems that share some analogous properties.

 

The Origins of Scaling in Cities
Lúis M. A. Bettencourt

SFI-WP 12-09-014

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The Algorithmic Origins of Life

Although it has been notoriously difficult to pin down precisely what it is that makes life so distinctive and remarkable, there is general agreement that its informational aspect is one key property, perhaps the key property. The unique informational narrative of living systems suggests that life may be characterized by context-dependent causal influences, and in particular, that top-down (or downward) causation -- where higher-levels influence and constrain the dynamics of lower-levels in organizational hierarchies -- may be a major contributor to the hierarchal structure of living systems. Here we propose that the origin of life may correspond to a physical transition associated with a shift in causal structure, where information gains direct, and context-dependent causal efficacy over the matter it is instantiated in. Such a transition may be akin to more traditional physical transitions (e.g. thermodynamic phase transitions), with the crucial distinction that determining which phase (non-life or life) a given system is in requires dynamical information and therefore can only be inferred by identifying causal architecture. We discuss some potential novel research directions based on this hypothesis, including potential measures of such a transition that may be amenable to laboratory study, and how the proposed mechanism corresponds to the onset of the unique mode of (algorithmic) information processing characteristic of living systems.

The Algorithmic Origins of Life
Sara Imari Walker, Paul C. W. Davies
http://arxiv.org/abs/1207.4803
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utopiah's comment, December 18, 2012 6:15 AM
Btw she recently made a SETI talk http://www.youtube.com/watch?v=dPiI4nYD0Vg
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Is Science Mostly Driven by Ideas or by Tools?

We are standing now as we stood in the 1950s, between a Kuhnian dream of sudden illumination and a Galisonian reality of laborious exploring. On one side are string theory and speculations about multiverses; on the other are all-sky surveys and observations of real black holes. The balance today is more even than it was in the 1950s. String theory is a far more promising venture than Einstein's unified field theory. Kuhn and Galison are running neck and neck in the race for glory. We are lucky to live in a time when both are going strong.

Is Science Mostly Driven by Ideas or by Tools?
Freeman J. Dyson
Science 14 December 2012:
Vol. 338 no. 6113 pp. 1426-1427
http://dx.doi.org/10.1126/science.1232773
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Ageing

Ageing is inevitable. Yet for centuries people have tried to slow or stop it, from bathing in the blood of virgin girls to concocting an elixir of life. These days, anti-ageing research is on a more scientific footing. And while we are no closer to finding the fountain of youth, humans — for a variety of reasons — are living longer than ever before

Ageing
Michelle Grayson
Nature 492, S1 (06 December 2012) http://dx.doi.org/10.1038/492S1a
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The Illusion of the Perpetual Money Machine

We argue that the present crisis and stalling economy continuing since 2007 are rooted in the delusionary belief in policies based on a "perpetual money machine" type of thinking. We document strong evidence that, since the early 1980s, consumption has been increasingly funded by smaller savings, booming financial profits, wealth extracted from house price appreciation and explosive debt. This is in stark contrast with the productivity-fueled growth that was seen in the 1950s and 1960s. This transition, starting in the early 1980s, was further supported by a climate of deregulation and a massive growth in financial derivatives designed to spread and diversify the risks globally. The result has been a succession of bubbles and crashes

The Illusion of the Perpetual Money Machine
D. Sornette, P. Cauwels
http://arxiv.org/abs/1212.2833
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Evidence for Non-Finite-State Computation in a Human Social System

Finite-State Machines are a basic model of computation, forming one of the simplest classes in the computational hierarchy. When given a probabilistic transition structure, they are one of the most common methods for description and prediction of symbolic time-series in the biological and social sciences. Here we show how a generalization of a central result for finite-state machines, the pumping lemma, to the probabilistic case, leads to a crucial constraint: sufficiently long sequences will be exponentially suppressed for finite-state processes. We apply the probabilistic pumping lemma to an analysis of behavioral patterns in the distributed, open-source Wikipedia community to demonstrate strong evidence for the emergence of functional powers over and above the regular grammars, and provide evidence to associate these with fundamentally interpersonal and social phenomena.

Evidence for Non-Finite-State Computation in a Human Social System
Simon DeDeo
http://arxiv.org/abs/1212.0018
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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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Complexity and the Limits of Revolution: What Will Happen to the Arab Spring?

The recent social unrest across the Middle East and North Africa has deposed dictators who had ruled for decades. While the events have been hailed as an "Arab Spring" by those who hope that repressive autocracies will be replaced by democracies, what sort of regimes will eventually emerge from the crisis remains far from certain. Here we provide a complex systems framework, validated by historical precedent, to help answer this question. We describe the dynamics of governmental change as an evolutionary process similar to biological evolution, in which complex organizations arise by replication, variation and competitive selection. Different kinds of governments, however, have differing levels of complexity. Democracies must be more systemically complex than autocracies because of their need to incorporate large numbers of people in decision-making. This difference has important implications for the relative robustness of democratic and autocratic governments after revolutions. Revolutions may disrupt existing evolved complexity, limiting the potential for building more complex structures quickly. Insofar as systemic complexity is reduced by revolution, democracy is harder to create in the wake of unrest than autocracy. Applying this analysis to the Middle East and North Africa, we infer that in the absence of stable institutions or external assistance, new governments are in danger of facing increasingly insurmountable challenges and reverting to autocracy.

Alexander S. Gard-Murray, Yaneer Bar-Yam, Complexity and the Limits of Revolution: What Will Happen to the Arab Spring? arXiv (in press) , December 11, 2012.
http://www.necsi.edu/research/social/revolutions/
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Complex social contagion makes networks more vulnerable to disease outbreaks

Social network analysis is now widely used to investigate the dynamics of infectious disease spread from person to person. Vaccination dramatically disrupts the disease transmission process on a contact network, and indeed, sufficiently high vaccination rates can disrupt the process to such an extent that disease transmission on the network is effectively halted. Here, we build on mounting evidence that health behaviors - such as vaccination, and refusal thereof - can spread through social networks through a process of complex contagion that requires social reinforcement. Using network simulations that model both the health behavior and the infectious disease spread, we find that under otherwise identical conditions, the process by which the health behavior spreads has a very strong effect on disease outbreak dynamics. This variability in dynamics results from differences in the topology within susceptible communities that arise during the health behavior spreading process, which in turn depends on the topology of the overall social network. Our findings point to the importance of health behavior spread in predicting and controlling disease outbreaks.

 

Complex social contagion makes networks more vulnerable to disease outbreaks

Ellsworth Campbell, Marcel Salathé

http://arxiv.org/abs/1211.0518

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Solving Complex Problems

Before he became America's first de facto science adviser and before he helped lay the foundation for the National Science Foundation, Vannevar Bush was a professor of Electrical Engineering and, eventually, dean of Engineering and vice president at the Massachusetts Institute of Technology (MIT). In those capacities, he came in contact with some of the nation's best and brightest minds in their formative years. But after two decades in such a rarified academic environment, Bush had become disenchanted by the increasing specialization of undergraduate curricula in science and engineering in America. He felt that education in these fields placed too much emphasis on information transferral from teacher to student and too little on deep understanding and intellectual synthesis by the student. Bush was among the first to anticipate that massive amounts of information would someday be universally and readily available to all, such that our ability to communicate knowledge through classes would become far less important than our ability to inspire students to do something creative, and valuable, with it.

 

Solving Complex Problems
K. V. Hodges

Science 30 November 2012:
Vol. 338 no. 6111 pp. 1164-1165
http://dx.doi.org/10.1126/science.1215228

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A Large-Scale Model of the Functioning Brain

A central challenge for cognitive and systems neuroscience is to relate the incredibly complex behavior of animals to the equally complex activity of their brains. Recently described, large-scale neural models have not bridged this gap between neural activity and biological function. In this work, we present a 2.5-million-neuron model of the brain (called “Spaun”) that bridges this gap by exhibiting many different behaviors. The model is presented only with visual image sequences, and it draws all of its responses with a physically modeled arm. Although simplified, the model captures many aspects of neuroanatomy, neurophysiology, and psychological behavior, which we demonstrate via eight diverse tasks.

 

A Large-Scale Model of the Functioning Brain
Chris Eliasmith, Terrence C. Stewart, Xuan Choo, Trevor Bekolay, Travis DeWolf, Yichuan Tang, Daniel Rasmussen

Science 30 November 2012:
Vol. 338 no. 6111 pp. 1202-1205
http://dx.doi.org/10.1126/science.1225266

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What the No Free Lunch Theorems Really Mean; How to Improve Search Algorithms

The NFL theorems have stimulated lots of subsequent work, with over 2500 citations of [12] alone by spring 2012 according to Google Scholar. However, arguably much of that research has missed the most important implications of the theorems. As stated in [12], the primary importance of the NFL theorems for search is what they tell us about “the underlying mathematical ‘skeleton’ of optimization theory before the ‘flesh’ of the probability distributions of a particular context and set of optimization problems are imposed”. So in particular, while the NFL theorems have strong implications if one believes in a uniform distribution over optimization problems, in no sense should they be interpreted as advocating such a distribution. In this short note I elaborate this perspective on what it is that is really important about the NFL theorems for search. I then discuss how the fact that there are NFL theorems for both search and for supervised learning is symptomatic of the deep formal relationship between those two fields. Once that relationship is disentangled, it suggests many ways that we can exploit practical techniques that were first developed in supervised learning to help us do search. I summarize some experiments that confirm the power of search algorithms developed in this way. I end by briefly discussing the various free lunch theorems that have been derived, and possible directions for future research.

 

Title: What the No Free Lunch Theorems Really Mean; How to Improve Search Algorithms
David H. Wolpert

SFI WP 12-10-017

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On the Foundations of the Theory of Evolution

Darwinism conceives evolution as a consequence of random variation and natural selection, hence it is based on a materialistic, i.e. matter-based, view of science inspired by classical physics. But matter in itself is considered a very complex notion in modern physics. More specifically, at a microscopic level, matter and energy are no longer retained within their simple form, and quantum mechanical models are proposed wherein potential form is considered in addition to actual form. In this paper we propose an alternative to standard Neodarwinian evolution theory. We suggest that the starting point of evolution theory cannot be limited to actual variation whereupon is selected, but to variation in the potential of entities according to the context. We therefore develop a formalism, referred to as Context driven Actualization of Potential (CAP), which handles potentiality and describes the evolution of entities as an actualization of potential through a reiterated interaction with the context.

 

On the Foundations of the Theory of Evolution

Diederik Aerts, Stan Bundervoet, Marek Czachor, Bart D'Hooghe, Liane Gabora, Philip Polk, Sandro Sozzo

http://arxiv.org/abs/1212.0107

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