Social Foraging
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Dynamics of Social Interaction
Curated by Ashish Umre
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Decision making in ant foragers (Lasius niger) facing conflicting private and social information

Decision making in ant foragers (Lasius niger) facing conflicting private and social information | Social Foraging | Scoop.it

Foragers of many ant species use pheromone trails to guide nestmates to food sources. During foraging, individual workers can also learn the route to a food source. Foragers of the mass-recruiting ant Lasius niger use both pheromone trails and memory to locate a food source. As a result, an experienced forager can have a conflict between social information (trail pheromones) and private information (route memory) at trail bifurcations. We tested decision making in L. niger foragers facing such an informational conflict in situations where both the strength of the pheromone trail and the number of previous visits to the food source varied. Foragers quickly learned the branch at a T bifurcation that leads to a food source, with 74.6% choosing correctly after one previous visit and 95.3% after three visits. Pheromone trails had a weaker effect on choice behaviour of naïve ants, with only 61.6% and 70.2% choosing the branch that had been marked by one or 20 foragers versus an unmarked branch. When there was a conflict between private and social information, memory overrides pheromone after just one previous visit to a food source. Most ants, 82–100%, chose the branch where they had collected food during previous foraging trips, with the proportion depending on the number of previous trips (1 v. 3) but not on the strength of the pheromone trail (1 v. 20). In addition, the presence of a pheromone trail at one branch in a bifurcation had no effect on the time it took an experienced ant to choose the correct branch (the branch without pheromone). These results suggest that private information (navigational memory) dominates over social information (chemical tail) in orientation decisions during foraging activities in experienced L. niger foragers.

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Social Learning in Insects — From Miniature Brains to Consensus Building

Communication and learning from each other are part of the success of insect societies. Here, we review a spectrum of social information usage in insects — from inadvertently provided cues to signals shaped by selection specifically for information transfer. We pinpoint the sensory modalities involved and, in some cases, quantify the adaptive benefits. Well substantiated cases of social learning among the insects include learning about predation threat and floral rewards, the transfer of route information using a symbolic ‘language’ (the honeybee dance) and the rapid spread of chemosensory preferences through honeybee colonies via classical conditioning procedures. More controversial examples include the acquisition of motor memories by observation, teaching in ants and behavioural traditions in honeybees. In many cases, simple mechanistic explanations can de identified for such complex behaviour patterns.

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Video: Discovery of the Spider That Builds Spider Decoys

Video: Discovery of the Spider That Builds Spider Decoys | Social Foraging | Scoop.it

In December, we reported on a new species of spider discovered in Peru. Tiny, and likely a new member of the genus Cyclosa, the spider builds large, spider-shaped decoys — and vibrates its web, acting as a master puppeteer.

Here is a video shot at the moment the spiders were discovered.

 

“I don’t know of any potential species discovery that has been caught on video to the same level that this one has been,” said the videographer who goes by Destin, who was accompanying biologist Phil Torres in the Peruvian Amazon.

 

“It’s fun to go back and watch the video because it reminds me of how confused and perplexed we were.”

 

Indeed, the captured moment of discovery includes the following exchange:

 

“It’s a tiny spider disguised as a big spider!”

 

“Shut up.”

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How Did Topological Data Analysis (TDA) Lead to the Birth of Ayasdi?

How Did Topological Data Analysis (TDA) Lead to the Birth of Ayasdi? | Social Foraging | Scoop.it

http://www.ayasdi.com/

 

Topological Data Analysis (TDA) brings together mathematics with computer science, and uses algorithms and concepts from algebraic topology to extract insights from complex multi-dimensional data structures. In more layman’s terms: Topological Data Analysis studies the underlying shape of data with the principle that “Data has Shape, Shape has Meaning.”

 

While Topological Data Analysis (TDA) may seem like something only for math people, Ayasdi’s founder and Stanford Mathematics Professor Gunnar Carlsson had a goal to make TDA into something that anyone could use without having a Ph.D. in mathematics.

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Ant foraging and geodesic paths in labyrinths: Analytical and computational results

Ant foraging and geodesic paths in labyrinths: Analytical and computational results | Social Foraging | Scoop.it

In this paper we propose a mechanism for the formation of paths of minimal length between two points (trails) by a collection of individuals undergoing reinforced random walks. This is the case, for instance, of ant colonies in search for food and the development of ant trails connecting nest and food source. Our mechanism involves two main ingredients: (1) the reinforcement due to the gradients in the concentration of some substance (pheromones in the case of ants) and (2) the persistence understood as the tendency to preferably follow straight directions in the absence of any external effect. Our study involves the formulation and analysis of suitable Markov chains for the motion in simple labyrinths, that will be understood as graphs, and numerical computations in more complex graphs reproducing experiments performed in the past with ants.

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Visual Data Mining of Biological Networks: One Size Does Not Fit All

Visual Data Mining of Biological Networks: One Size Does Not Fit All | Social Foraging | Scoop.it

High-throughput technologies produce massive amounts of data. However, individual methods yield data specific to the technique used and biological setup. The integration of such diverse data is necessary for the qualitative analysis of information relevant to hypotheses or discoveries. It is often useful to integrate these datasets using pathways and protein interaction networks to get a broader view of the experiment. The resulting network needs to be able to focus on either the large-scale picture or on the more detailed small-scale subsets, depending on the research question and goals. In this tutorial, we illustrate a workflow useful to integrate, analyze, and visualize data from different sources, and highlight important features of tools to support such analyses.

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Neuroscientist Says Green Consciousness Is in Right Brain

Neuroscientist Says Green Consciousness Is in Right Brain | Social Foraging | Scoop.it

When neuroscientist Dr. Jill Bolte Taylor had a stroke that put her logical, sequential left brain temporarily out of commission, she experienced a temporary state of peaceful, all-connected consciousness that changed her forever. She described this in her best-selling book My Stroke of Insight: A Brain Scientist's Personal Journey. At first she saw this intuitive and wholistic right brain state as crucial to human mental health but after a visit to Antarctica with Al Gore she began to see how it might also offer clues about how a desperately-needed new eco-consciousness might be as close as the right side of our brains. She describes this in a Jan. 4, 2013 Huffington Post story, "Does Our Planet Need a Stroke of Insight"?

 

But how to experience this right-brain eco-connection without having to go through a potentially deadly stroke?

 

The idea of using various methods for accessing the right brain isn't new, of course. Far from it. But the recent emphasis seems to have been on how to connect with this side of ourselves merely so we can succeed at some left brain activity like business or goal-oriented sports.

 

Taylor's critical insight is that by entering this altered, nonlinear state of consciousness we may reconnect with an important awareness that, when combined with the more practical, rational left-brain insights of science, might allow us to more effectively address our current environmental situation.

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A Mathematical Approach to Safeguarding Private Data

A Mathematical Approach to Safeguarding Private Data | Social Foraging | Scoop.it
A mathematical technique called “differential privacy” gives researchers access to vast repositories of personal data while meeting a high standard for privacy protection.

 

In 1997, when Massachusetts began making health records of state employees available to medical researchers, the government removed patients’ names, addresses, and Social Security numbers. William Weld, then the governor, assured the public that identifying individual patients in the records would be impossible.

 

Within days, an envelope from a graduate student at the Massachusetts Institute of Technology arrived at Weld’s office. It contained the governor’s health records.

 

Although the state had removed all obvious identifiers, it had left each patient’s date of birth, sex and ZIP code. By cross-referencing this information with voter-registration records, Latanya Sweeney was able to pinpoint Weld’s records.

 

Sweeney’s work, along with other notable privacy breaches over the past 15 years, has raised questions about the security of supposedly anonymous information.

 

“We’ve learned that human intuition about what is private is not especially good,” said Frank McSherry of Microsoft Research Silicon Valley in Mountain View, Calif. “Computers are getting more and more sophisticated at pulling individual data out of things that a naive person might think are harmless.”

 

As awareness of these privacy concerns has grown, many organizations have clamped down on their sensitive data, uncertain about what, if anything, they can release without jeopardizing the privacy of individuals. But this attention to privacy has come at a price, cutting researchers off from vast repositories of potentially invaluable data.

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Toyota's Semi-Autonomous Car Will Keep You Safe

Toyota's Semi-Autonomous Car Will Keep You Safe | Social Foraging | Scoop.it

At a CES press conference yesterday, Toyota presented its semi-autonomous Lexus Advanced Active Safety Research Vehicle, a car designed to take over from you when an accident is imminent to keep you in one piece.

 

To be clear, this is a research vehicle, and it's not designed to turn into a Google-style autonomous car. It's more about a high-level of driver assistance, with the car using sensors and intelligence to augment what its human driver is doing. Think of it as a co-pilot, essentially, there to point things out and give you help when you need it.

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4th International Workshop on Modeling Social Media: Mining, Modeling and Recommending 'Things' in Social Media - Workshop at Hypertext 2013

In our first workshop on Modeling Social Media (MSM 2010 in Toronto, Canada), we explored various different models of social media ranging from user modeling, hypertext models, software engineering models, sociological models and framework models. In our second workshop (MSM 2011 in Boston, USA), we addressed the user interface aspects of modeling social media. In our third workshop (MSM 2012 in Milwaukee, USA), we looked at the collective intelligence in social media, i.e. making sense of the content and context from social media websites such as Facebook, Twitter, Google+ and Foursquare by analyzing tweets, tags, blog posts, likes, posts and check-ins, in order to create a new knowledge and semantic meaning. With this year's workshop we aim to attract researchers from all over the world working in the field of social media mining, modeling and end-user applications. In particular, we would like to invite researchers working on the important field of "recommender systems" for social media which is gaining more and more in importance due to the increasing information overload problem. 


The goal of this workshop is to continue our vibrant discussion on social media mining and modelling with a special focus on recommender systems for social media applications. Hence, the workshop aims to attract and discuss various novel aspects of social media mining, modelling and doing recommendations on top of these data/models. In short the workshop invites topics such as social media mining methods/techniques, novel approaches to model users or things in social media, frameworks to harvest and/or display social media data and new social media recommender methods/techniques/algorithms or interfaces supporting users for instance in information finding, meta-data application etc. Thus, our goal is to bring together researchers and practitioners from all over the world with diverse backgrounds interested in 1) exploring different perspectives and approaches to mine (complex) and analyse social media data, 2) modelling social media users and 3) building applications such as recommender systems on top of this data/models.

Ashish Umre's insight:
Submission deadlinesPaper Submission:Monday, February 04, 2013Acceptance Notification:Monday, February 18, 2013Paper Final Version Due: Thursday, February 28, 2013Workshop: May 01, 2013
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Biomimicry Solves Age-old Industrial Air Pollution Problem

Biomimicry Solves Age-old Industrial Air Pollution Problem | Social Foraging | Scoop.it

Enter inventor Matthew Johnson from the Department of Chemistry at theUniversity of Copenhagen. "Biomimicry" may not be the perfect term to describe what Johnson did, which mimics how Mother Nature cleans Earth's atmosphere rather than how any particular life-form works, but the concept of copying natural processes seems to fit in the category. Johnson describes his inspiration:


"I have investigated the self-cleaning mechanism of the atmosphere for years. Suddenly I realized, that the mechanism is so simple, that we could wrap it in a box and use it to clean indoor air. This makes for a better indoor climate, and in this particular case it also removes smells from this industrial process allowing the company to stay and making the neighbours happy."

 

Earth's atmosphere cleans itself when polluting gasses plus sunlight plus naturally occurring ozone cause the pollutants to clump together as particles, which can then be washed out in the next rain.

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The Materiality of Algorithms

The Materiality of Algorithms | Social Foraging | Scoop.it

One of the most exciting aspects of the new research analyzing algorithmic culture is the manner by which portions of that research are increasingly routing around the slow, painful process of traditional academic knowledge production. This is not to say that the credentialing process afforded by peer-reviewed journals or university presses is irrelevant, but it is to say that this aspect of scholarly work is only one form among the many others now emerging both on- and offline.  Overviews of stand-alone talks are now available through a variety of blogs, while a double session at this year’s 4S on “The Politics of Algorithms” was illuminating for those of us lucky enough to attend.  Journals like Limn blur the boundaries between old and new forms of scholarship. All of this is just a long way of saying that, since I first alluded to the notion of a “sociology of algorithms” in 2011, I’ve been stimulated by my contact with a much wider community doing great work on these issues, much of which I’ve encountered through this very blog.

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Cognitive benefit of lifelong bilingualism

Seniors who have spoken two languages since childhood are faster than single-language speakers at switching from one task to another, according to a study published in the January 9 issue of The Journal of Neuroscience. Compared to their monolingual peers, lifelong bilinguals also show different patterns of brain activity when making the switch, the study found.


The findings suggest the value of regular stimulating mental activity across the lifetime. As people age, cognitive flexibility -- the ability to adapt to unfamiliar or unexpected circumstances -- and related "executive" functions decline. Recent studies suggest lifelong bilingualism may reduce this decline -- a boost that may stem from the experience of constantly switching between languages. However, how brain activity differs between older bilinguals and monolinguals was previously unclear.

 

In the current study, Brian T. Gold, PhD, and colleagues at the University of Kentucky College of Medicine, used functional magnetic resonance imaging (fMRI) to compare the brain activity of healthy bilingual seniors (ages 60-68) with that of healthy monolingual seniors as they completed a task that tested their cognitive flexibility. The researchers found that both groups performed the task accurately. However, bilingual seniors were faster at completing the task than their monolingual peers despite expending less energy in the frontal cortex -- an area known to be involved in task switching.


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Alexandra Strickland's curator insight, September 12, 2013 7:13 AM

Fascinating insight into bilingualism and its impact on your life!

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Uncovering the complexity of ant foraging trail

The common garden ant Lasius niger use both trail pheromones and memory of past visits to navigate to and from food sources. In a recent paper we demonstrated a synergistic effect between route memory and trail pheromones: the presence of trail pheromones results in experienced ants walking straighter and faster. We also found that experienced ants leaving a pheromone trail deposit less pheromone. Here we focus on another finding of the experiment: the presence of cuticular hydrocarbons (CHCs), which are used as home range markers by ants, also affects pheromone deposition behavior. When walking on a trail on which CHCs are present but trail pheromones are not, experienced foragers deposit less pheromone on the outward journey than on the return journey. The regulatory mechanisms ants use during foraging and recruitment behavior is subtle and complex, affected by multiple interacting factors such as route memory, travel direction and the presence trail pheromone and home-range markings.

 

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Synergy between social and private information increases foraging efficiency in ants

Insect societies integrate many information sources to organize collective activities such as foraging. Many ants use trail pheromones to guide foragers to food sources, but foragers can also use memories to find familiar locations of stable food sources. Route memories are often more accurate than trail pheromones in guiding ants, and are often followed in preference to trail pheromones when the two conflict. Why then does the system expend effort in producing and acquiring seemingly redundant and low-quality information, such as trail pheromones, when route memory is available? Here we show that, in the ant Lasius niger, trail pheromones and route memory act synergistically during foraging; increasing walking speed and straightness by 25 and 30 per cent, respectively, and maintaining trail pheromone deposition, but only when used together. Our results demonstrate a previously undescribed major role of trail pheromones: to complement memory by allowing higher confidence in route memory. This highlights the importance of multiple interacting information sources in the efficient running of complex adaptive systems.

 

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John Herndon's curator insight, February 15, 2013 2:26 PM

Management lesson from nature: Encourage your employees to take your guidance to heart, but give them automony and safety to find their own path to get the job done. The individual's own approach may be more efficient and productive for their personality style. Promote sharing of lessons learned. This will form a self supporting guidance system which will become the foundation for the future individuals that need to complete a similar task.

 

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Facebook's Bold, Compelling and Scary Engine of Discovery: The Inside Story of Graph Search

Beast had a birthday last week. The First Dog of social networking — live-in companion to Mark Zuckerberg and his bride, Priscilla Chan — turned two. The proud owners baked a cake for the Hungarian sheepdog and decided to throw an impromptu party. Naturally, when it came time to compile the guest list, the couple turned to Facebook, the $67 billion company that Zuckerberg founded in his dorm room nine years ago.

 

To date, sorting through your Facebook friends could be a frustrating task. Although the site has a search bar, there has been no easy way to quickly cull contacts based on specific criteria. But Zuckerberg was testing a major new feature that Facebook would announce on Jan. 15 — one that promises to transform its user experience, threaten its competitors, and torment privacy activists. It’s called Graph Search, and it will eventually allow a billion people to dive into the vast trove of stored information about them and their network of friends. In Zuckerberg’s case, it allowed him to type “Friends of Priscilla and me who live around Palo Alto” and promptly receive a list of potential celebrants. “We invited five people over who were obvious dog lovers,” he says.

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OCE Postdoctoral Fellowship - Evolutionary Aerial Robotics @ CSIRO, Brisbane, Australia

CSIRO ICT Centre's Autonomous Systems Lab is offering a prestigious OCE Postdoctoral Fellowship for a talented and dedicated recent (or near) PhD graduate with experience in the fields of Evolutionary Computing and/or Aerial Robotics.


The successful candidatewill work on a new project in Evolutionary Aerial Robotics (EAR) with the objective of developing autonomous Unmanned Aircraft Systems(UAS) that create and evolve their own autonomy systems (i.e. the UAS “brain”), and thereby shortcutting and outperforming the expensive and time-consuming classical engineering approach.


This is an interdisciplinary project that is concerned with developing novel autonomy technologies that will allow future Unmanned UAS to exhibit advanced autonomous behaviours using artificial evolution algorithms. This will include research and development of novel or improved evolutionary algorithms for UAS, applying them to a variety of aspects including flight control, bio-inspired navigation, 3D obstacle avoidance, failure detection and autonomy architectures.

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'Good Times' brainwave app blocks phone calls when the user is busy, wins 1st prize ($30,000) of AT&T Hackathon

'Good Times' brainwave app blocks phone calls when the user is busy, wins 1st prize ($30,000) of AT&T Hackathon | Social Foraging | Scoop.it
Developed in 24 hours only, 'Good Times', a brain-controlled application connects to the Necomimi brainwave cat ears and blocks phone calls when the user is busy at work or a conversation.
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Approximate Bayesian Computation

Approximate Bayesian Computation | Social Foraging | Scoop.it

Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics. In all model-based statistical inference, the likelihood function is of central importance, since it expresses the probability of the observed data under a particular statistical model, and thus quantifies the support data lend to particular values of parameters and to choices among different models. For simple models, an analytical formula for the likelihood function can typically be derived. However, for more complex models, an analytical formula might be elusive or the likelihood function might be computationally very costly to evaluate. ABC methods bypass the evaluation of the likelihood function. In this way, ABC methods widen the realm of models for which statistical inference can be considered. ABC methods are mathematically well-founded, but they inevitably make assumptions and approximations whose impact needs to be carefully assessed. Furthermore, the wider application domain of ABC exacerbates the challenges of parameter estimation and model selection. ABC has rapidly gained popularity over the last years and in particular for the analysis of complex problems arising in biological sciences (e.g., in population genetics, ecology, epidemiology, and systems biology).

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Computer, electrical engineers working to help biologists cope with big data

Computer, electrical engineers working to help biologists cope with big data | Social Foraging | Scoop.it
Liang Dong held up a clear plastic cube, an inch or so across, just big enough to hold 10 to 20 tiny seeds.

 

Using sophisticated sensors and software, researchers can precisely control the light, temperature, humidity and carbon dioxide inside that cube.

 

Dong -- an Iowa State University assistant professor of electrical and computer engineering, of chemical and biological engineering and an associate of the U.S. Department of Energy's Ames Laboratory -- calls it a "microsystem instrument." Put hundreds of those cubes together and researchers can simultaneously grow thousands of seeds and seedlings in different conditions and see what happens. How, for example, do the plants react when it is hot and dry? Or carbon dioxide levels change? Or light intensity is adjusted very slightly?

 

The instrument designed and built by Dong's research group will keep track of all that by using a robotic arm to run a camera over the cubes and take thousands of images of the growing seeds and seedlings.

 

Plant scientists will use the images to analyze the plants' observable characteristics -- the leaf color, the root development, the shoot size. All those observations are considered a plant's phenotype. And while plant scientists understand plant genetics very well, Dong said they don't have a lot of data about how genetics and environment combine to influence phenotype.

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Researchers use data from traffic app to identify high frequency accident locations

Ben-Gurion University of the Negev (BGU) researchers reveal that data culled from geosocial networks like the GPS traffic app Waze can help prevent traffic incidents with better deployment of police resources at the most accident prone areas.

 

Only now are we beginning to discover the potential in the huge amount of data collected daily," explains BGU researcher and Ph.D. student Michael Fire. "Studies of this kind, which monitor events such as traffic accidents over time, can help the police identify dangerous sections of roads in real time, or alternatively, locations where few police are needed."

 

The paper, "Data Mining Opportunities in Geosocial Networks for Improving Road Safety," was presented at the IEEE 27th Convention of Electrical and Electronics Engineers in Israel. Waze records location data and enables users to upload and share comments on any detail, including traffic alerts, accidents or police presence. According to its Web site, Waze has 30 million worldwide users and describes itself as "a community-based traffic and navigation app whose users share real-time traffic and road info, saving time and gas money."

"Only now are we beginning to discover the potential in the huge amount of data collected daily," explains BGU researcher and Ph.D. student Michael Fire. "Studies of this kind, which monitor events such as traffic accidents over time, can help the police identify dangerous sections of roads in real time, or alternatively, locations where few police are needed."

Read more at: http://phys.org/news/2013-01-traffic-app-high-frequency-accident.html#jCp"Only now are we beginning to discover the potential in the huge amount of data collected daily," explains BGU researcher and Ph.D. student Michael Fire. "Studies of this kind, which monitor events such as traffic accidents over time, can help the police identify dangerous sections of roads in real time, or alternatively, locations where few police are needed." The paper, "Data Mining Opportunities in Geosocial Networks for Improving Road Safety," was presented at the IEEE 27th Convention of Electrical and Electronics Engineers in Israel. Waze records location data and enables users to upload and share comments on any detail, including traffic alerts, accidents or police presence. According to its Web site, Waze has 30 million worldwide users and describes itself as "a community-based traffic and navigation app whose users share real-time traffic and road info, saving time and gas money."

Read more at: http://phys.org/news/2013-01-traffic-app-high-frequency-accident.html#jCp
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Hybridization of Evolutionary Algorithms

Evolutionary algorithms are good general problem solver but suffer from a lack of domain specific knowledge. However, the problem specific knowledge can be added to evolutionary algorithms by hybridizing. Interestingly, all the elements of the evolutionary algorithms can be hybridized. In this chapter, the hybridization of the three elements of the evolutionary algorithms is discussed: the objective function, the survivor selection operator and the parameter settings. As an objective function, the existing heuristic function that construct the solution of the problem in traditional way is used. However, this function is embedded into the evolutionary algorithm that serves as a generator of new solutions.

 

In addition, the objective function is improved by local search heuristics. The new neutral selection operator has been developed that is capable to deal with neutral solutions, i.e. solutions that have the different representation but expose the equal values of objective function. The aim of this operator is to directs the evolutionary search into a new undiscovered regions of the search space. To avoid of wrong setting of parameters that control the behavior of the evolutionary algorithm, the self-adaptation is used. Finally, such hybrid self-adaptive evolutionary algorithm is applied to the two real-world NP-hard problems: the graph 3-coloring and the optimization of markers in the clothing industry. Extensive experiments shown that these hybridization improves the results of the evolutionary algorithms a lot. Furthermore, the impact of the particular hybridizations is analyzed in details as well.

  
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Cheating slime mold gets the upper hand

Cheating slime mold gets the upper hand | Social Foraging | Scoop.it

A  ‘cheater’ mutation (chtB) inDictyostelium discoideum, a free living slime mould able to co-operate as social organism when food is scarce, allows the cheater strain to exploit its social partner, finds a new study published in BioMed Central’s open access journal BMC Evolutionary Biology. The mutation ensures that when mixed with ‘normal’ Dictyostelium  more than the fair share of cheaters become spores, dispersing to a new environment, and avoiding dying as stalk cells. 

Dictyostelium have an unusual life style. They generally live as individual amoeboid cells, eating bacteria in leaf litter and soil. However when they run out of food they form a multi-cellular ‘slug’ capable of travelling to a new environment. However if conditions are right they behave more like a fungus, producing a stalk and a fruiting body which releases spores. During this co-operative behaviour approximately 20% become stalk cells which are doomed to starvation but, after dispersal, the spores germinate into new amoeba.

The chtB strain is able to reduce the ability of normalDictyostelium to form spores so that when mixed in equal numbers with wild type Dictyostelium 60% of the spores will be chtB. The chtB mutation appeared to be normal in all other respects and the mutation had no ‘fitness cost’ which might impede its behaviour or lifespan. In fact the mutation allowed chtB to divide faster in liquid medium.

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Biomimicry: sharkskin ships and whale flipper wind turbines

Biomimicry: sharkskin ships and whale flipper wind turbines | Social Foraging | Scoop.it
From the splendour of a peacock’s feathers to the aerodynamic body of a cheetah, natural selection has worked to engineer animals to the highest standards for survival and prosperity in their environment. Throughout history, humans have tried to emulate the wonders and beauty of the natural world in science, design and art. 

Over the past 20 years, however, this process of learning from and emulating nature has developed into a defined scientific discipline and burgeoning industry, known as “biomimicry”. 

People have always looked to nature for inspiration. In the sixteenth century, Leonardo Da Vinci made detailed sketches of birds’ anatomy to better understand the science of flight and foster ideas for his “flying machine”. The Wright brothers, over 400 years later, were still studying birds’ wings, as a potential model for the first airplane.

Yet it was only in 1997 that the term “biomimicry” was coined, and the concept really began to take off as a serious practice in the business world.

The term “biomimicry” was first used by the American biologist and authorJanine Benyus, in her book Biomimicry: Innovation Inspired by Nature. She defines biomimicry, not merely as learning “about” the natural world, but learning “from” it. Benyus calls this “the conscious emulation of life’s genius”.
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Artificial Intelligence in Motion: Introduction to Recommendations with Map-Reduce and mrjob

Artificial Intelligence in Motion: Introduction to Recommendations with Map-Reduce and mrjob | Social Foraging | Scoop.it

I will present how can we use map-reduce programming model for making recommendations.   Recommender systems are quite popular among shopping sites and social network thee days. How do they do it ?   Generally, the user interaction data available from items and products in shopping sites and social networks are enough information to build a recommendation engine using classic techniques such as Collaborative Filtering.

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