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Showing posts with label behavior. Show all posts
Showing posts with label behavior. Show all posts

Thursday, March 28, 2013

Dead Sparrow Turned into Robot to Study Bird Behavior

Sparrow

Researchers at Duke University recently took a major step toward better understanding how swamp sparrows use a combination of song and visual displays to communicate with one another. How they came about making this discovery, though, is what makes this story particularly newsworthy — they stuffed a deceased swamp sparrow with a miniature computer and some robotics to give it the ability to flap its wings as if it were alive.

Duke biologist Rindy Anderson led a team of biologists on the study, receiving technical assistance from engineering undergraduate student David Perch. The team brought “Robosparrow,” as it is aptly referred to, to a swamp sparrow breeding ground and placed it in the territories of live males.

Once all systems were go, the robotic bird “sang” swamp sparrow songs vis-à-vis a nearby sound system that let the birds know it was intruding on their ground. Anderson observed from a distance, sitting amid the tall swampy grasses, and changed the bird’s behavior to study various responses. They had it sing in a stationary position, shift side to side, and as mentioned before, flap its wings.

What they found was a song combined with wing waves is more potent than song alone, and that wing waves by themselves evoked the most aggressive response from live male birds.

“What I didn’t expect to see was that the birds would give strikingly similar aggressive wing-wave signals to the three types of invaders,” Anderson said. That is to say, she thought the defending birds would simply match the signals of the intruding robosparrow. What they instead discovered was that the males are more individualistic and consistent in the level of aggressiveness that they want to signal.

“That response makes sense, in retrospect, since attacks can be devastating,” she said. What Anderson means by this is that male swamp sparrows only want to signal a certain level of aggression to see if they can scare off an intruder without provoking any sort of physical conflict that could result in severe injury or death. Some sparrows were intimidated by robosparrow’s flapping, while others responded with a more aggressive flapping pattern.

Also worth noting from this study is that whether the robosparrow waved its wings or not, some live male sparrows still came in and attacked it. “It’s high stakes for these little birds. They only live a couple of years, and most only breed once a year, so owning a territory and having a female is high currency,” Anderson said.

Looking ahead, Anderson and her team plan to further test how the sparrows use wing waves combined with a characteristic twitter called “soft-song” to show aggression and fend off competition. Unfortunately, it’s going to take some time before the bot gets back in the field, as robosparrow’s motor is burned out from its last run, and the bird’s head was ripped off during one of the attacks.

 Source: duke.edu, electronicproducts.com

Reference:

Anderson, R., DuBois, A., Piech, D., Searcy, W., & Nowicki, S. (2013). Male response to an aggressive visual signal, the wing wave display, in swamp sparrows Behavioral Ecology and Sociobiology DOI: 10.1007/s00265-013-1478-9


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Saturday, September 15, 2012

'Anternet' discovered: Behavior of harvester ants as they forage for food mirrors protocols that control Internet traffic

ScienceDaily (Aug. 28, 2012) — On the surface, ants and the Internet don't seem to have much in common. But two Stanford researchers have discovered that a species of harvester ants determine how many foragers to send out of the nest in much the same way that Internet protocols discover how much bandwidth is available for the transfer of data. The researchers are calling it the "anternet."

Deborah Gordon, a biology professor at Stanford, has been studying ants for more than 20 years. When she figured out how the harvester ant colonies she had been observing in Arizona decided when to send out more ants to get food, she called across campus to Balaji Prabhakar, a professor of computer science at Stanford and an expert on how files are transferred on a computer network. At first he didn't see any overlap between his and Gordon's work, but inspiration would soon strike.

"The next day it occurred to me, 'Oh wait, this is almost the same as how [Internet] protocols discover how much bandwidth is available for transferring a file!'" Prabhakar said. "The algorithm the ants were using to discover how much food there is available is essentially the same as that used in the Transmission Control Protocol."

Transmission Control Protocol, or TCP, is an algorithm that manages data congestion on the Internet, and as such was integral in allowing the early web to scale up from a few dozen nodes to the billions in use today. Here's how it works: As a source, A, transfers a file to a destination, B, the file is broken into numbered packets. When B receives each packet, it sends an acknowledgment, or an ack, to A, that the packet arrived.

This feedback loop allows TCP to run congestion avoidance: If acks return at a slower rate than the data was sent out, that indicates that there is little bandwidth available, and the source throttles data transmission down accordingly. If acks return quickly, the source boosts its transmission speed. The process determines how much bandwidth is available and throttles data transmission accordingly.

It turns out that harvester ants (Pogonomyrmex barbatus) behave nearly the same way when searching for food. Gordon has found that the rate at which harvester ants -- which forage for seeds as individuals -- leave the nest to search for food corresponds to food availability.

A forager won't return to the nest until it finds food. If seeds are plentiful, foragers return faster, and more ants leave the nest to forage. If, however, ants begin returning empty handed, the search is slowed, and perhaps called off.

Prabhakar wrote an ant algorithm to predict foraging behavior depending on the amount of food -- i.e., bandwidth -- available. Gordon's experiments manipulate the rate of forager return. Working with Stanford student Katie Dektar, they found that the TCP-influenced algorithm almost exactly matched the ant behavior found in Gordon's experiments.

"Ants have discovered an algorithm that we know well, and they've been doing it for millions of years," Prabhakar said.

They also found that the ants followed two other phases of TCP. One phase is known as slow start, which describes how a source sends out a large wave of packets at the beginning of a transmission to gauge bandwidth; similarly, when the harvester ants begin foraging, they send out foragers to scope out food availability before scaling up or down the rate of outgoing foragers.

Another protocol, called time-out, occurs when a data transfer link breaks or is disrupted, and the source stops sending packets. Similarly, when foragers are prevented from returning to the nest for more than 20 minutes, no more foragers leave the nest.

Prabhakar said that had this discovery been made in the 1970s, before TCP was written, harvester ants very well could have influenced the design of the Internet.

Gordon thinks that scientists have just scratched the surface for how ant colony behavior could help us in the design of networked systems.

There are 11,000 species of ants, living in every habitat and dealing with every type of ecological problem, Gordon said. "Ants have evolved ways of doing things that we haven't thought up, but could apply in computer systems. Computationally speaking, each ant has limited capabilities, but the collective can perform complex tasks.

"So ant algorithms have to be simple, distributed and scalable -- the very qualities that we need in large engineered distributed systems," she said. "I think as we start understanding more about how species of ants regulate their behavior, we'll find many more useful applications for network algorithms."

The work is published in the Aug. 23 issue of PLoS Computational Biology.

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The above story is reprinted from materials provided by Stanford University. The original article was written by Bjorn Carey.

Note: Materials may be edited for content and length. For further information, please contact the source cited above.

Journal Reference:

Balaji Prabhakar, Katherine N. Dektar, Deborah M. Gordon. The Regulation of Ant Colony Foraging Activity without Spatial Information. PLoS Computational Biology, 2012; 8 (8): e1002670 DOI: 10.1371/journal.pcbi.1002670

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.


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Monday, September 10, 2012

Search engine for social networks based on the behavior of ants

ScienceDaily (June 4, 2012) — Research at Carlos III University (Universidad Carlos III) in Madrid (Universidad Carlos III -- UC3M) is developing an algorithm, based on ants' behavior when they are searching for food, which accelerates the search for relationships among elements that are present in social networks.

One of the main technical questions in the field of social networks, whose use is becoming more and more generalized, consists in locating the chain of reference that leads from one person to another, from one node to another. The greatest challenges that are presented in this area is the enormous size of these networks and the fact that the response must be rapid, given that the final user expects results in the shortest time possible. In order to find a solution to this problem, these researchers from UC3M have developed an algorithm SoSACO, which accelerates the search for routes between two nodes that belong to a graph that represents a social network.

The way SoSACO works was inspired by behavior that has been perfected over thousands of years by one of the most disciplined insects on the planet when they search for food. In general, the algorithms used by colonies of ants imitate how they are capable of finding the path between the anthill and the source of food by secreting and following a chemical trail, called a pheromone, which is deposited on the ground.

"In this study -- the authors explain -- other scented trails are also included so that the ants can follow both the pheromone as well as the scent of the food, which allows them to find the food source much more quickly." The main results of this research, which was carried out by Jessica Rivero in UC3M's Laboratorio de Bases de Datos Avanzadas (The Advanced Data Bases Laboratory -- LABDA) as part of her doctoral thesis, are summarized in a scientific article published in the journal Applied Intelligence. "The early results show that the application of this algorithm to real social networks obtains an optimal response in a very short time (tens of milliseconds)," Jessica Rivero states.

Multiple applications

Thanks to this new search algorithm, the system can find these routes more easily, and without modifying the structure of graph (an image that uses nodes and links to represents the relationships among a set of elements). "This advance allows us to solve many problems that we find in the real world, because the scenarios in which they occur can be modeled by a graph," the researchers explain. Thus, it could be applied in many different scenarios, such as to improve locating routes in FPS systems or in on-line games, to plan deliveries for freight trucks, to know if two words are somehow related or to simply know exactly which affinities two Facebook or Twitter users, for example, have in common.

This research, which has received support from the Autonomous Community of Madrid (MA2VICMR, S2009/TIC-1542) and the Ministry of Education and Science (Ministerio de Educación y Ciencia), began as part of the SOPAT project (TSI-020110-2009-419), in response to the need to guide a hotel's clients using a natural interaction system. Jessica Rivero's doctoral thesis, which deals with this subject, is titled "Búsqueda Rápida de Caminos en Grafos de Alta Cardinalidad Estáticos y Dinámicos" ("A Quick Search for Routes in Static and Dynamic Graphs of High Cardinality"); it was directed by Francisco Javier Calle y Mª Dolores Cuadra, professors in the LABDA of the Computer Science Department, and received a grade of Apto-Cum Laude (Pass-Cum Laude).

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The above story is reprinted from materials provided by Universidad Carlos III de Madrid - Oficina de Información Científica, via AlphaGalileo.

Note: Materials may be edited for content and length. For further information, please contact the source cited above.

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.


View the original article here

Thursday, July 19, 2012

Search engine for social networks based on the behavior of ants

ScienceDaily (June 4, 2012) — Research at Carlos III University (Universidad Carlos III) in Madrid (Universidad Carlos III -- UC3M) is developing an algorithm, based on ants' behavior when they are searching for food, which accelerates the search for relationships among elements that are present in social networks.

One of the main technical questions in the field of social networks, whose use is becoming more and more generalized, consists in locating the chain of reference that leads from one person to another, from one node to another. The greatest challenges that are presented in this area is the enormous size of these networks and the fact that the response must be rapid, given that the final user expects results in the shortest time possible. In order to find a solution to this problem, these researchers from UC3M have developed an algorithm SoSACO, which accelerates the search for routes between two nodes that belong to a graph that represents a social network.

The way SoSACO works was inspired by behavior that has been perfected over thousands of years by one of the most disciplined insects on the planet when they search for food. In general, the algorithms used by colonies of ants imitate how they are capable of finding the path between the anthill and the source of food by secreting and following a chemical trail, called a pheromone, which is deposited on the ground.

"In this study -- the authors explain -- other scented trails are also included so that the ants can follow both the pheromone as well as the scent of the food, which allows them to find the food source much more quickly." The main results of this research, which was carried out by Jessica Rivero in UC3M's Laboratorio de Bases de Datos Avanzadas (The Advanced Data Bases Laboratory -- LABDA) as part of her doctoral thesis, are summarized in a scientific article published in the journal Applied Intelligence. "The early results show that the application of this algorithm to real social networks obtains an optimal response in a very short time (tens of milliseconds)," Jessica Rivero states.

Multiple applications

Thanks to this new search algorithm, the system can find these routes more easily, and without modifying the structure of graph (an image that uses nodes and links to represents the relationships among a set of elements). "This advance allows us to solve many problems that we find in the real world, because the scenarios in which they occur can be modeled by a graph," the researchers explain. Thus, it could be applied in many different scenarios, such as to improve locating routes in FPS systems or in on-line games, to plan deliveries for freight trucks, to know if two words are somehow related or to simply know exactly which affinities two Facebook or Twitter users, for example, have in common.

This research, which has received support from the Autonomous Community of Madrid (MA2VICMR, S2009/TIC-1542) and the Ministry of Education and Science (Ministerio de Educación y Ciencia), began as part of the SOPAT project (TSI-020110-2009-419), in response to the need to guide a hotel's clients using a natural interaction system. Jessica Rivero's doctoral thesis, which deals with this subject, is titled "Búsqueda Rápida de Caminos en Grafos de Alta Cardinalidad Estáticos y Dinámicos" ("A Quick Search for Routes in Static and Dynamic Graphs of High Cardinality"); it was directed by Francisco Javier Calle y Mª Dolores Cuadra, professors in the LABDA of the Computer Science Department, and received a grade of Apto-Cum Laude (Pass-Cum Laude).

Share this story on Facebook, Twitter, and Google:

Other social bookmarking and sharing tools:

Story Source:

The above story is reprinted from materials provided by Universidad Carlos III de Madrid - Oficina de Información Científica, via AlphaGalileo.

Note: Materials may be edited for content and length. For further information, please contact the source cited above.

Note: If no author is given, the source is cited instead.

Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.


View the original article here