Darwinian Ascension
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A simple model clarifies the complicated relationships of complex networks

Researchers have discovered many types of complex networks and have proposed hundreds of models to explain their origins, yet most of the relationships within each of these types are still uncertain. Furthermore, because of the large number of types and models of complex networks, it is widely thought that these complex networks cannot all share a simple universal explanation. However, here we find that a simple model can produce many types of complex networks, including scale-free, small-world, ultra small-world, Delta-distribution, compact, fractal, regular and random networks, and by revising this model, we show that one can produce community-structure networks. Using this model and its revised versions, the complicated relationships among complex networks can be illustrated. Given that complex networks are regarded as a model tool of complex systems, the results here bring a new perspective to understanding the power law phenomena observed in various complex systems.

 

A simple model clarifies the complicated relationships of complex networks

Bojin Zheng, Hongrun Wu, Jun Qin, Wenhua Du, Jianmin Wang, Deyi Li

http://arxiv.org/abs/1210.3121


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Evolution Is Moving Us Away from Selfishness. But Where Is It Taking Us? | Big Think

Evolution Is Moving Us Away from Selfishness. But Where Is It Taking Us? | Big Think | Darwinian Ascension | Scoop.it
Renowned medical researcher Dr. Rudolph Tanzi takes you on a tour of the brain, and explains why positive thinking might be the best gift you can give your genes this holiday season.
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From residue coevolution to protein conformational ensembles and functional dynamics

From residue coevolution to protein conformational ensembles and functional dynamics | Darwinian Ascension | Scoop.it
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Homophyly/Kinship Model: Naturally Evolving Networks

Homophyly/Kinship Model: Naturally Evolving Networks | Darwinian Ascension | Scoop.it
It has been a challenge to understand the formation and roles of social groups or natural communities in the evolution of species, societies and real world networks.
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Glia-derived neurons are required for sex-specific learning in C. elegans : Nature : Nature Publishing Group

Glia-derived neurons are required for sex-specific learning in C. elegans : Nature : Nature Publishing Group | Darwinian Ascension | Scoop.it
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Arjen ten Have's curator insight, October 27, 2015 10:24 AM

Luckily we are not worms. Or are we? The message is that males prefer sex over a meal and that women prefer sustenance. In terms of evolution this does make sense. Does that explain why men are better cooks? A Dutch proverb goes "The love of a man comes through the stomach" Well, that is apparently not the best way of putting it.

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Death by Design? Spatial models show that natural selection favors genetically-limited lifespan as a lineal benefit

Death by Design? Spatial models show that natural selection favors genetically-limited lifespan as a lineal benefit | Darwinian Ascension | Scoop.it
(Phys.org)—Standard evolutionary theories of aging and mortality, being based on mean-field assumptions – which analyze the behavior of large and complex stochastic models by studying a simpler model – conclude that programmed mortality resulting from natural selection is impossible. Recently, however, scientists at the New England Complex Systems Institute, and the Wyss Institute for Biologically Inspired Engineering at Harvard University, both in Cambridge, Massachusetts, using spatial models with local rather than globally-uniform reproduction, demonstrated that programmed deaths strongly result in long-term benefit to an organismal lineage by reducing local environmental resource depletion over many generations. (In spatial models, variables are distributed in space such that actions can affect the local environment without affecting the global environment.) Moreover, the researchers found that these results continued to be favored when a large number of variations related to different real-world factors were applied to the spatial model, which they say supports their approach being applicable to a wide range of biological systems, and therefore that direct selection for shorter life span may be quite widespread in nature.
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With Mindware Upgrades and Cognitive Prosthetics, Humans Are Already Technological Animals

With Mindware Upgrades and Cognitive Prosthetics, Humans Are Already Technological Animals | Darwinian Ascension | Scoop.it
In recent years, the surprising idea that we’ll one day merge with our technology has warily made its way into the mainstream. Often it’s couched in a combination of snark and fear. Why in the world would we want to do that? It’s so inhuman.

That the idea is distasteful isn’t shocking. The imagination rapidly conjures images of Star Trek’s Borg, a nightmarish future when humans and machines melt into a monstrosity of flesh and wires, forever and irrevocably leaving “nature” behind.

But let’s not fool ourselves with such dark fantasies. Humans are already technological animals; tight integration with our inventions is in our nature; and further increasing that integration won’t take place in some distant future—it’s happening now.

To observe our technological attachment, we need simply walk out the door. It’s everywhere, all around us—on the bus or train, at work, at home, in the bathroom, in bed—people gazing into screens, living digital lives right next to their ordinary ones.

In the Matrix, the experience is involuntary, a tool of control and oppression. In our world, it’s voluntary, and mostly about freedom, expansion, and expression. As Jason Silva recently noted, our devices augment our brains, like cognitive prosthetics.

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Table of Contents — July 22, 2014, 111 (Supplement 3)

Table of Contents — July 22, 2014, 111 (Supplement 3) | Darwinian Ascension | Scoop.it
Arjen ten Have's insight:

More than ten papers of Darwinian Thinking in the Social Sciences. Enjoy your weekend!

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Detecting Communities Based on Network Topology

Detecting Communities Based on Network Topology | Darwinian Ascension | Scoop.it

Network methods have had profound influence in many domains and disciplines in the past decade. Community structure is a very important property of complex networks, but the accurate definition of a community remains an open problem. Here we defined community based on three properties, and then propose a simple and novel framework to detect communities based on network topology. We analyzed 16 different types of networks, and compared our partitions with Infomap, LPA, Fastgreedy and Walktrap, which are popular algorithms for community detection. Most of the partitions generated using our approach compare favorably to those generated by these other algorithms. Furthermore, we define overlapping nodes that combine community structure with shortest paths. We also analyzed the E. Coli. transcriptional regulatory network in detail, and identified modules with strong functional coherence.

  


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Ivon Prefontaine's curator insight, July 26, 2014 6:54 PM

Community is a more complex and organic organizing than teams. Teams are inherently hierarchical with predetermined goals. Communities are fluid and the goals are continuously being negotiated. Schools and classrooms are better served to be thought of as communities with overlapping qualities and permeable boundaries with other communities.

Eli Levine's curator insight, July 29, 2014 6:42 PM

A useful tool for policy making, because it helps identify communities and how they interact to form super-communities.

 

The essence of mapping the polity and the public, socially, economically, technologically, and infrastrucutrally.

 

Think about it.

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Towards the Standard Model of Evolution

Towards the Standard Model of Evolution | Darwinian Ascension | Scoop.it
The so-called Modern Synthesis of Evolution was shaped by men like Fisher, Dobzhansky, and Wright, somewhere in the mid 20th century. A lot has happened since then but I cannot say things have become
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Emergence and persistence of communities in coevolutionary networks

We investigate the emergence and persistence of communities through a recently proposed mechanism of adaptive rewiring in coevolutionary networks. We characterize the topological structures arising in a coevolutionary network subject to an adaptive rewiring process and a node dynamics given by a simple voterlike rule. We find that, for some values of the parameters describing the adaptive rewiring process, a community structure emerges on a connected network. We show that the emergence of communities is associated to a decrease in the number of active links in the system, i.e. links that connect two nodes in different states. The lifetime of the community structure state scales exponentially with the size of the system. Additionally, we find that a small noise in the node dynamics can sustain a diversity of states and a community structure in time in a finite size system. Thus, large system size and/or local noise can explain the persistence of communities and diversity in many real systems.

 

Emergence and persistence of communities in coevolutionary networks
J. C. González-Avella, M. G. Cosenza, J. L. Herrera, K. Tucci

http://arxiv.org/abs/1407.0388


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Context effects produced by question orders reveal quantum nature of human judgments

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Arjen ten Have's curator insight, June 16, 2014 9:26 PM
So do you still believe in free will? I must say, this flabbergasts me but this is just sooooooooooo nice. Good start of the week! In recent years, quantum probability theory has been used to explain a range of seemingly irrational human decision-making behaviors. The quantum models generally outperform traditional models in fitting human data, but both modeling approaches require optimizing parameter values. However, quantum theory makes a universal, nonparametric prediction for differing outcomes when two successive questions (e.g., attitude judgments) are asked in different orders. Quite remarkably, this prediction was strongly upheld in 70 national surveys carried out over the last decade (and in two laboratory experiments) and is not one derivable by any known cognitive constraints. The findings lend strong support to the idea that human decision making may be based on quantum probability
Mel Melendrez-Vallard's curator insight, June 17, 2014 8:17 AM

Great Insight from Arjen ten Have's:

"So do you still believe in free will? I must say, this flabbergasts me but this is just sooooooooooo nice. Good start of the week! In recent years, quantum probability theory has been used to explain a range of seemingly irrational human decision-making behaviors. The quantum models generally outperform traditional models in fitting human data, but both modeling approaches require optimizing parameter values. However, quantum theory makes a universal, nonparametric prediction for differing outcomes when two successive questions (e.g., attitude judgments) are asked in different orders. Quite remarkably, this prediction was strongly upheld in 70 national surveys carried out over the last decade (and in two laboratory experiments) and is not one derivable by any known cognitive constraints. The findings lend strong support to the idea that human decision making may be based on quantum probability"
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Simulations Reveal How White Lies Glue Society Together and Black Lies Create Diversity

Simulations Reveal How White Lies Glue Society Together and Black Lies Create Diversity | Darwinian Ascension | Scoop.it

Evolutionary biologists have long thought that lying ought to destroy societies. Now computational anthropologists have shown that nothing could be further from the truth.

 

Everybody learns as a child that lying is wrong. We all learn something else too—that some kinds of lies are worse than others. What’s more, certain kinds of fibs—so-called white lies– are actually quite acceptable, even necessary at times.

 

Consequently, humans become sophisticated liars. Indeed, various studies have shown that we lie all the time, perhaps as often as twice a day on average.

 

It’s easy to see how lying reduces the level of trust between individuals and so threatens the stability of societies. So how do societies survive all this lying?

 

That’s something of a puzzle for evolutionary biologists. The very fact that lying is so prevalent in human society suggests that it might offer some kind of evolutionary advantage. In other words, we all benefit from lying in some way. But how?

 

Today, we get an answer thanks to the work of Gerardo Iñiguez at Aalto University in Finland and a few pals (including Robin Dunbar, an anthropologist from the University of Oxford of Dunbar’s number fame). These guys have simulated the effect that lies have on the strength of connections that exist within a social network.

 

But they’ve added fascinating twist. These guys have made a clear distinction between lies that benefit the person being lied to versus lies that benefit the person doing the lying. In other words, their model captures the difference between “white” lies, which are prosocial, and “black” lies, which are antisocial.


Via Ashish Umre
Arjen ten Have's insight:

Interesting although it holds no real surprises, this is one of the things that just needed confirmation. Obviously white and black lies both have their explanation in evolution. A white lie helps you because you help the other, the black lie because you don't. Is to so hard or strange to understand? Fun stuff though!

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Cyborg-Like Bionics Harness Sunlight | EE Times

Cyborg-Like Bionics Harness Sunlight | EE Times | Darwinian Ascension | Scoop.it
Terminator cyborgs may be on the horizon as a result of bionics supra-particles invented at the University of Michigan and Pittsburgh.
Arjen ten Have's insight:

This is not my actual idea of ascension but I must admit it might help. Then why isn't this my idea of human ascension? Well although science on itself is neutral, its impact for sure isn't. Technology is great and great things can be achieved but since I have a hard time accepting we are ready for real group selection, where group equals complete human society, I am afraid this technology will be first used by NSA and other US military organizations. Science fiction will come true but I am not so sure that the plastic (as in flexible) human will actually prevail. So should we stop or fear this? No we should guide it,  just as we guide for nuclear proliferance (albeit that it would be better if the nuclear states would at least reduce their stocks).

 

I'll be back!

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The complexity of biodiversity: A biological perspective on economic valuation

Arjen ten Have's insight:

Cool stuff! We should think in the value of biodiversity rather than reemplacement of the elder.

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System that replaces human intuition with algorithms outperforms human teams

System that replaces human intuition with algorithms outperforms human teams | Darwinian Ascension | Scoop.it
Big-data analysis consists of searching for buried patterns that have some kind of predictive power. But choosing which "features" of the data to analyze usually requires some human intuition. In a database containing, say, the beginning and end dates of various sales promotions and weekly profits, the crucial data may not be the dates themselves but the spans between them, or not the total profits but the averages across those spans.
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Crowded growth leads to the spontaneous evolution of semistable coexistence in laboratory yeast populations

Arjen ten Have's insight:

Now how should we understand or translate this type of research when investigating humn evolution.

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Higher social class predicts increased unethical behavior

Higher social class predicts increased unethical behavior | Darwinian Ascension | Scoop.it
Arjen ten Have's insight:

Obviously it will be important to define Higher social class and I will not be surprised if here it is directly related to income. In that case I am not surprised but still it is good to really demonstrate the obvious.

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Site-specific group selection drives locally adapted group compositions

Group selection may be defined as selection caused by the differential extinction or proliferation of groups. The socially polymorphic spider Anelosimus studiosus exhibits a behavioural polymorphism in which females exhibit either a ‘docile’ or ‘aggressive’ behavioural phenotype. Natural colonies are composed of a mixture of related docile and aggressive individuals, and populations differ in colonies’ characteristic docile:aggressive ratios. Using experimentally constructed colonies of known composition, here we demonstrate that population-level divergence in docile:aggressive ratios is driven by site-specific selection at the group level—certain ratios yield high survivorship at some sites but not others. Our data also indicate that colonies responded to the risk of extinction: perturbed colonies tended to adjust their composition over two generations to match the ratio characteristic of their native site, thus promoting their long-term survival in their natal habitat. However, colonies of displaced individuals continued to shift their compositions towards mixtures that would have promoted their survival had they remained at their home sites, regardless of their contemporary environment. Thus, the regulatory mechanisms that colonies use to adjust their composition appear to be locally adapted. Our data provide experimental evidence of group selection driving collective traits in wild populations.

 

Site-specific group selection drives locally adapted group compositions
• Jonathan N. Pruitt & Charles J. Goodnight

Nature 514, 359–362 (16 October 2014) http://dx.doi.org/10.1038/nature1381


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Arjen ten Have's insight:

Now the really interesting part would be of course to explain this emergent groups selection by gene selection. How do we define or, if you wish, describe the Evolutionary Stable Strategy that is behind this interesting phenomenon. What can we as human society learn from this?

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Artificial intelligence: the next step in evolution? - The Age

Artificial intelligence: the next step in evolution? - The Age | Darwinian Ascension | Scoop.it
Artificial intelligence: the next step in evolution?
The Age
American philosopher Daniel Dennett sums up the feelings of some scientists when suggesting that humans are immensely complex and able computational machines.
Arjen ten Have's insight:

Cool elaboration  on AI. Quote:“When we start to design intelligent systems to include motives and the emotional signalling that accompanies them – and to use these as a reference standard against which perceived events and objects can be sorted, evaluated and organised – we’ll have made a major step towards achieving true machine intelligence.”

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Using sociometers to quantify social interaction patterns

Using sociometers to quantify social interaction patterns | Darwinian Ascension | Scoop.it
Research on human social interactions has traditionally relied on self-reports. Despite their widespread use, self-reported accounts of behaviour are prone to biases and necessarily reduce the range of behaviours, and the number of subjects, that may be studied simultaneously. The development of ever smaller sensors makes it possible to study group-level human behaviour in naturalistic settings outside research laboratories. We used such sensors, sociometers, to examine gender, talkativeness and interaction style in two different contexts. Here, we find that in the collaborative context, women were much more likely to be physically proximate to other women and were also significantly more talkative than men, especially in small groups. In contrast, there were no gender-based differences in the non-collaborative setting. Our results highlight the importance of objective measurement in the study of human behaviour, here enabling us to discern context specific, gender-based differences in interaction style.

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Cooperating with the future

Overexploitation of renewable resources today has a high cost on the welfare of future generations. Unlike in other public goods games, however, future generations cannot reciprocate actions made today. What mechanisms can maintain cooperation with the future? To answer this question, we devise a new experimental paradigm, the /`Intergenerational Goods Game/'. A line-up of successive groups (generations) can each either extract a resource to exhaustion or leave something for the next group. Exhausting the resource maximizes the payoff for the present generation, but leaves all future generations empty-handed. Here we show that the resource is almost always destroyed if extraction decisions are made individually. This failure to cooperate with the future is driven primarily by a minority of individuals who extract far more than what is sustainable. In contrast, when extractions are democratically decided by vote, the resource is consistently sustained. Voting is effective for two reasons. First, it allows a majority of cooperators to restrain defectors. Second, it reassures conditional cooperators that their efforts are not futile. Voting, however, only promotes sustainability if it is binding for all involved. Our results have implications for policy interventions designed to sustain intergenerational public goods.

 

Cooperating with the future
Oliver P. Hauser, David G. Rand, Alexander Peysakhovich & Martin A. Nowak

Nature 511, 220–223 (10 July 2014) http://dx.doi.org/10.1038/nature13530


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Tom Cockburn's curator insight, July 31, 2014 3:26 AM

Optimistic,in lab at least?

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Grand Challenges for Evolutionary Robotics

Evolutionary Robotics is a field that “aims to apply evolutionary computation techniques to evolve the overall design or controllers, or both, for real and simulated autonomous robots” (Vargas et al., 2014). This approach is “useful both for investigating the design space of robotic applications and for testing scientific hypotheses of biological mechanisms and processes” (Floreano et al., 2008). However, as noted in Bongard (2013) “the use of metaheuristics (i.e., evolution) sets this subfield of robotics apart from the mainstream of robotics research,” which “aims to continuously generate better behavior for a given robot, while the long-term goal of Evolutionary Robotics is to create general, robot-generating algorithms.”

 

Front. Robot. AI, 30 June 2014 | http://dx.doi.org/10.3389/frobt.2014.00004

Grand challenges for evolutionary robotics
Agoston E. Eiben


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Swarm intelligence inspired shills and the evolution of cooperation

Swarm intelligence inspired shills and the evolution of cooperation | Darwinian Ascension | Scoop.it
Many hostile scenarios exist in real-life situations, where cooperation is disfavored and the collective behavior needs intervention for system efficiency improvement. Towards this end, the framework of soft control provides a powerful tool by introducing controllable agents called shills, who are allowed to follow well-designed updating rules for varying missions. Inspired by swarm intelligence emerging from flocks of birds, we explore here the dependence of the evolution of cooperation on soft control by an evolutionary iterated prisoner's dilemma (IPD) game staged on square lattices, where the shills adopt a particle swarm optimization (PSO) mechanism for strategy updating. We demonstrate that not only can cooperation be promoted by shills effectively seeking for potentially better strategies and spreading them to others, but also the frequency of cooperation could be arbitrarily controlled by choosing appropriate parameter settings. Moreover, we show that adding more shills does not contribute to further cooperation promotion, while assigning higher weights to the collective knowledge for strategy updating proves a efficient way to induce cooperative behavior. Our research provides insights into cooperation evolution in the presence of PSO-inspired shills and we hope it will be inspirational for future studies focusing on swarm intelligence based soft control.

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The Effect of Social Learning on Individual Learning and Evolution

We consider the effects of social learning on the individual learning and genetic evolution of a colony of artificial agents capable of genetic, individual and social modes of adaptation. We confirm that there is strong selection pressure to acquire traits of individual learning and social learning when these are adaptive traits. We show that selection pressure for learning of either kind can supress selection pressure for reproduction or greater fitness. We show that social learning differs from individual learning in that it can support a second evolutionary system that is decoupled from the biological evolutionary system. This decoupling leads to an emergent interaction where immature agents are more likely to engage in learning activities than mature agents.

 

The Effect of Social Learning on Individual Learning and Evolution
Chris Marriott, Jobran Chebib

http://arxiv.org/abs/1406.2720


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