Swarm Behavior and Starling Theory

  Swarm Behavior

Starling Theory

Excerpts from National Geographic

A single ant or bee isn’t smart, but their colonies are. The study of swarm intelligence is providing insights that can help humans manage complex systems.

Harmonious Flight

The ability of animal groups-such as this flock of starlings-to shift shape as one, even when they have no leader, reflects the genius of collective behavior-something scientists are now tapping to solve human problems.

Social and political groups have already adopted crude swarm tactics.

During mass protests eight years ago in Seattle, anti-globalization activists used mobile communications devices to spread news quickly about police movements, turning an otherwise unruly crowd into a “smart mob” that was able to disperse and re-form like a school of fish.

The biggest changes may be on the Internet. Consider the way Google uses group smarts to find what you’re looking for. When you type in a search query, Google surveys billions of Web pages on its index servers to identify the most relevant ones. It then ranks them by the number of pages that link to them, counting links as votes (the most popular sites get weighted votes, since they’re more likely to be reliable). The pages that receive the most votes are listed first in the search results. In this way, Google says, it “uses the collective intelligence of the Web to determine a page’s importance.”

Wikipedia, a free collaborative encyclopedia, has also proved to be a big success, with millions of articles in more than 200 languages about everything under the sun, each of which can be contributed by anyone or edited by anyone. “It’s now possible for huge numbers of people to think together in ways we never imagined a few decades ago,” says Thomas Malone of MIT’s new Center for Collective Intelligence. “No single person knows everything that’s needed to deal with problems we face as a society, such as health care or climate change, but collectively we know far more than we’ve been able to tap so far.”

Such thoughts underline an important truth about collective intelligence:

Crowds tend to be wise only if individual members act responsibly and make their own decisions.

  • A group won’t be smart if its members_
    • imitate one another,
    • slavishly follow fads,
    • or wait for someone to tell them what to do.
  • When a group is being intelligent,
    • whether it’s made up of ants
    • or attorneys,
    • it relies on its members to do their own part.
  • For those of us who sometimes wonder_
    • if it’s really worth recycling that extra bottle to lighten our impact on the planet,
    • the bottom line is that our actions matter,
    • even if we don’t see how.

Think about a honeybee as she walks around inside the hive.

  • If a cold wind hits the hive, she’ll shiver to generate heat and, in the process, help to warm the nearby brood.
  • She has no idea that hundreds of workers in other parts of the hive are doing the same thing at the same time to the benefit of the next generation.

    “A honeybee never sees the big picture any more than you or I do,” says Thomas Seeley, the bee expert.

  • “None of us knows what society as a whole needs,
    • but we look around and say, oh,
    • they need someone to volunteer at school,
    • or mow the church lawn,
    • or help in a political campaign.”

I used to think ants knew what they were doing. The ones marching across my kitchen counter looked so confident, I just figured they had a plan, knew where they were going and what needed to be done. How else could ants organize highways, build elaborate nests, stage epic raids, and do all the other things ants do?

Turns out I was wrong.

  • Ants aren’t clever little engineers,
  • architects,
  • or warriors after all-at least not as individuals.
  • When it comes to deciding what to do next, most ants don’t have a clue.

“If you watch an ant try to accomplish something, you’ll be impressed by how inept it is,” says Deborah M. Gordon, a biologist at Stanford University.

How do we explain, then, the success of Earth’s 12,000 or so known ant species? They must have learned something in 140 million years.

“Ants aren’t smart,” Gordon says. “Ant colonies are.” A colony can solve problems unthinkable for individual ants, such as_

  • finding the shortest path to the best food source,
  • allocating workers to different tasks,
  • or defending a territory from neighbors.

As individuals, ants might be tiny dummies,

but as colonies

  • they respond quickly
  • and effectively to their environment.
  • They do it with something called swarm intelligence.

Where this intelligence comes from raises a fundamental question in nature:

How do the simple actions of individuals add up to the complex behavior of a group?

  • How do hundreds of honeybees make a critical decision about their hive if many of them disagree?
  •  What enables a school of herring to coordinate its movements so precisely it can change direction in a flash, like a single, silvery organism?

The collective abilities of such animals-

  • none of which grasps the big picture,
  • but each of which contributes to the group’s success-
  • seem miraculous even to the biologists who know them best. Yet during the past few decades, researchers have come up with intriguing insights.

One key to an ant colony, for example, is that_

  • No one’s in charge.
  • No generals command ant warriors.
  • No managers boss ant workers.
  • The queen plays no role except to lay eggs.
  • Even with half a million ants, a colony functions just fine with no management at all-at least none that we would recognize.

It relies instead upon countless interactions between individual ants, each of which is following simple rules of thumb. Scientists describe such a system as self-organizing.

Consider the problem of job allocation. In the Arizona desert where Deborah Gordon studies red harvester ants (Pogonomyrmex barbatus), a colony calculates each morning how many workers to send out foraging for food.

  • The number can change, depending on conditions.
  • Have foragers recently discovered a bonanza of tasty seeds?
  • More ants may be needed to haul the bounty home.
  •  Was the nest damaged by a storm last night?
  • Additional maintenance workers may be held back to make repairs.
  • An ant might be a nest worker one day, a trash collector the next.

But how does a colony make such adjustments if no one’s in charge? Gordon has a theory.

Ants communicate by touch and smell. When one ant bumps into another, it sniffs with its antennae to find out if the other belongs to the same nest and where it has been working. (Ants that work outside the nest smell different from those that stay inside.) Before they leave the nest each day, foragers normally wait for early morning patrollers to return. As patrollers enter the nest, they touch antennae briefly with foragers.

“When a forager has contact with a patroller, it’s a stimulus for the forager to go out,” Gordon says. “But the forager needs several contacts

WHEN IT COMES TO SWARM intelligence, ants aren’t the only insects with something useful to teach us. On a small, breezy island off the southern coast of Maine, Thomas Seeley, a biologist at Cornell University, has been looking into the uncanny ability of honeybees to make good decisions.

  • With as many as 50,000 workers in a single hive,
  • honeybees have evolved ways to work through individual differences of opinion to do what’s best for the colony.

If only people could be as effective in_

  • boardrooms,
  • church committees,
  • and town meetings,
  • Seeley says, we could avoid problems making decisions in our own lives.

The bees’ rules for decision-making-

  • seek a diversity of options,
  • encourage a free competition among ideas,
  • and use an effective mechanism to narrow choices-
  • so impressed Seeley that he now uses them at Cornell as chairman of his department.

“I’ve applied what I’ve learned from the bees to run faculty meetings,” he says. To avoid going into a meeting with his mind made up, hearing only what he wants to hear, and pressuring people to conform, Seeley asks his group to identify all the possibilities, kick their ideas around for a while, then vote by secret ballot. “It’s exactly what the swarm bees do, which gives a group time to let the best ideas emerge and win. People are usually quite amenable to that.”

In fact, almost any group that follows the bees’ rules will make itself smarter, says James Surowiecki, author of The Wisdom of Crowds. “The analogy is really quite powerful. The bees are predicting which nest site will be best, and humans can do the same thing, even in the face of exceptionally complex decisions.” Investors in the stock market, scientists on a research project, even kids at a county fair guessing the number of beans in a jar can be smart groups, he says, if their members are diverse, independent minded, and use a mechanism such as voting, auctioning, or averaging to reach a collective decision.

THERE’S A SMALL PARK near the White House in Washington, D.C., where I like to watch flocks of pigeons swirl over the traffic and trees. Sooner or later, the birds come to rest on ledges of buildings surrounding the park. Then something disrupts them, and they’re off again in synchronized flight.

The birds don’t have a leader.

No pigeon is telling the others what to do.

Instead, they’re each paying close attention to the pigeons next to them, each bird following simple rules as they wheel across the sky. These rules add up to another kind of swarm intelligence-one that has less to do with making decisions than with precisely coordinating movement.

By demonstrating the power of self-organizing models to mimic swarm behavior, Reynolds was also blazing the trail for robotics engineers. A team of robots that could coordinate its actions like a flock of birds could offer significant advantages over a solitary robot. Spread out over a large area, a group could function as a powerful mobile sensor net, gathering information about what’s out there. If the group encountered something unexpected, it could adjust and respond quickly, even if the robots in the group weren’t very sophisticated, just as ants are able to come up with various options by trial and error. If one member of the group were to break down, others could take its place. And, most important, control of the group could be decentralized, not dependent on a leader.

“In biology, if you look at groups with large numbers, there are very few examples where you have a central agent,” says Vijay Kumar, a professor of mechanical engineering at the University of Pennsylvania. “Everything is very distributed: They don’t all talk to each other. They act on local information. And they’re all anonymous. I don’t care who moves the chair, as long as somebody moves the chair. To go from one robot to multiple robots, you need all three of those ideas.”

The bees’ rules for decision-making-seek a diversity of options, encourage a free competition among ideas, and use an effective mechanism to narrow choices-so impressed Seeley that he now uses them at Cornell as chairman of his department.

“I’ve applied what I’ve learned from the bees to run faculty meetings,” he says.

  • To avoid going into a meeting with his mind made up,
  • hearing only what he wants to hear,
  • and pressuring people to conform,
  • Seeley asks his group to identify all the possibilities,
  • kick their ideas around for a while,
  • then vote by secret ballot.
  • “It’s exactly what the swarm bees do, which gives a group time to let the best ideas emerge and win. People are usually quite amenable to that.”

In fact, almost any group that follows the bees’ rules will make itself smarter, says James Surowiecki, author of The Wisdom of Crowds. “The analogy is really quite powerful. The bees are predicting which nest site will be best, and humans can do the same thing, even in the face of exceptionally complex decisions.” Investors in the stock market, scientists on a research project, even kids at a county fair guessing the number of beans in a jar can be smart groups, he says, if their members are diverse, independent minded, and use a mechanism such as voting, auctioning, or averaging to reach a collective decision.
no more than ten seconds apart before it will go out.”

That’s how swarm intelligence works:

simple creatures following simple rules,

  • each one acting on local information.
  • No ant sees the big picture.
  • No ant tells any other ant what to do.

Some ant species may go about this with more sophistication than others. (Temnothorax albipennis, for example, can rate the quality of a potential nest site using multiple criteria.) But the bottom line, says Iain Couzin, a biologist at Oxford and Princeton Universities, is that no leadership is required. “Even complex behavior may be coordinated by relatively simple interactions,” he says.

Inspired by the elegance of this idea, Marco Dorigo, a computer scientist at the Université Libre in Brussels, used his knowledge of ant behavior in 1991 to create mathematical procedures for solving particularly complex human problems, such as routing trucks, scheduling airlines, or guiding military robots.

“As soon as the wolf got within a certain distance of the caribou, the herd’s alertness just skyrocketed,” Karsten says. “Now there was no movement.

  • Every animal just stopped, completely vigilant and watching.”
  • A hundred yards (90 meters) closer, and the wolf crossed another threshold.

“The nearest caribou turned and ran, and that response moved like a wave through the entire herd until they were all running. Reaction times shifted into another realm. Animals closest to the wolf at the back end of the herd looked like a blanket unraveling and tattering, which, from the wolf’s perspective, must have been extremely confusing.”

The wolf chased one caribou after another, losing ground with each change of target. In the end, the herd escaped over the ridge, and the wolf was left panting and gulping snow.

For each caribou, the stakes couldn’t have been higher, yet the herd’s evasive maneuvers displayed not panic but precision. (Imagine the chaos if a hungry wolf were released into a crowd of people.)

Every caribou knew_

  • when it was time to run
  • and in which direction to go,
  • even if it didn’t know exactly why.
  • No leader was responsible for coordinating the rest of the herd.
  • Instead each animal was following simple rules evolved over thousands of years of wolf attacks.

That’s the wonderful appeal of swarm intelligence.

Whether we’re talking about_

  • ants,
  • bees,
  • pigeons,
  • or caribou,

the ingredients of smart group behavior-

  • decentralized control,
  • response to local cues,
  • simple rules of thumb-
  • add up to a shrewd strategy to cope with complexity.

Analysing Burma’s Democracy Revolution,Part 1 (in Burmese)

Comments

Aung Myint Kyi said _

I like your idea because we do not need to mention violence or non – violence which  one is better when we perform for democracy in Burma . Thank you for reminding all revolutionist so that  they can make less mistake. I agree that pre-thinking is the best for future.

Thiha said _

I’d like to suggest that to all revolutionist. There’s not important to WHO’S RIGHT but WHAT’S RIGHT.
Then we could get what we should do. Even we’re different race or religion but that’s doesn’t matter what we are. We should realize that what we are looking for. Our GOAL’S TOO.  We’re only ONE NATION. We shouldn’t compare to each other but compare to Internationally. Nowdays our nation’s very poor in the region. That’s nobody can deny. Please think about what we should do, please don’t think about what I can do. I agree that pre-thinking is the best for future.

Analysing Burma’s Democracy Revolution,Part 2 (in Burmese)

Comment:

Ko said _

               That is the best idea.

Thiha said _

I’m thank U to BURMA DIGEST Organization for our younger generation can know about our country’s past. Then we couldn’t mistake twice and shouldn’t again as well.

 

Analysing Burma’s Democracy Revolution,Part 3 (IN BURMESE)

Burma Game Plan (Burmese translation)

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                1 ? EkdifiHupm;uGuf (1)

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           2 ? EdkifiHa&;upm;uGuf (2)

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             jidrf;csrf;a&; ,lxm;aom vufeufukdifrsm;&,f ppftpkd;&ESif@ yl;aygif; aqmif&Guf aeaom EdkifiHa&;orm;rsm; taejzif@ ppftpkd;&ESif@ vrf;cGJaom enf;AsL[m ukdusif@okH;&ef vkdygonf ? okd@aomf xkdetz =oZmcHrsm; onfcGJxGufr_ukd tcsdefrSD rvkyfyJ etz ESif@ ylaygif;aeaoma=umif@ axmif 15 ESpfuscHae&aom tusOf;om;. tjzpfrsKd;ukd =uKHae&jyD ? olwkd@vnf;epfemjyD; olwkd@ukd,fpm;jyKygonf qkdaom vlrsKd;pkrsm;vnf; etz . ypfy,f acsmifxkd;r_ukd cHae&ygjyD ?

             3 ? EkdifiHa&; upm;uGuf (3)

            wkdif;&if;om;vlrsKd;pkrsm;&J@ EkdifiHa&;upm;uGif;ukd wcsufokH;oyf=unf@=uOD;pkd@?

             ucsif / u,m; / u&if / &Srf; / rGef / &ckdif tp&Sdonf@ tzG@Jrsm;ESif@ tjcm;vlrsKd;pk tzG@Ji,frsm;&J@ tajctaeukd =unf@ygu ppftpkd;&u tm%mcGJay;&ef nif;qkdcH&jyD;csdefwGif ppftpkd;&ESif@ tquftoG,f jzwfI tcsif;csif;eD;uyfpGmyl;aygif;aqmif&Guf=u&ef ta&;=uD;onf ?          

              tcsKyfom;ESpfOD;pvkH; ajzmif@csufay;ovkd tajctaeayg@? AkdvfwifOD;u ajzmif@csufay;rSawm@ Akdvfcifn$ef@ vnf;zGif@ajym&awm@rayg@ ? rajym&ifcH&rSmayg@ / ‘gayrJ@ wkdif;&if;om;vlrsdK;pkawGu tqkd;qkH; EkdifiHa&;AsL[mukd usifhokH;rd ae=ujyD ? tcsif;csif;rnDn$wfwJ@ tjyif wcsKd@u etz eJ@vufwGJae=uw,f?

              etz ppftpkd;&ukd z,fxm;jyD; wenf;=unf@=uOD;pkd@ ?

              wkdif;&if;om;vlrsKd;pkrsm; / olykefrsm; / ajray:ajratmuf ‘Drkdua&pDv_yf&Sm;olrsm; / trsKd;om;’Drkdua&pDtzGJcsKyfwkd@ ESifhf@ wEdkifiHvkH;&Sd jynfolrsm;ukd =unf@=u&r,f ? tcsKyfom;&J@ tajctae Oyrmt& olwkd@tm;vkH;twGuf taumif;qkH;enf;AsL[muawm@  – yl;aygif;aqmif&Gufa&;yJ ?

             ‘gayrJ@ v$rf;rkd;vkdaom 0g’ u r_dif;wkdufaeojzif@ –

            vlay:vlaZmfvkyf&ef / bESbl;okdufwl;olrsm;u tcsif;csif; tn$ef@cl;&ef tjrwfxkwf&ef =uHae=uonf ? r[wWr *END &J@vlxktm%mzDqefr_ / tpkd;&ESif@ yl;aygif;aqmif&Gufr_ jzwfawmufr_wkd@ukd rvkyfbJ opPmazgufaeol wcsKd@uazgufae=uonf?

             etz owif;ay; vkyfoluvkyfonf ? etz &J@pm;=uGif;pm;usef t&kd;t&if; ukduf&Edk;Ekd;ESif@ zm;ae=uonf ? wOD; csif; zGJ@ csif; aeESif@wukd,faumif;qefaomvkyf&yfrsm;u wEkdifiHvkH;. ta&;ukdopPmazgufovkd jzpfaejyD ? olwkd@twGuf tusKd;aus;Zl; tenf; i,f&aomfvnf; wEdkifiHvkH;twGuf qkH;&_H;r_=uD;jzpfaeonf ?

          4 ?  EdkifiHa&;upm;uGufjrifuGif; (4)

                twkduftcH ESifh bmoma&;tzGJ@rsm;jrifuGif;ayg@ ?

              tm;vkH;taumif;qkH;jzpfzkd@uawm@ tm;vkH;nDn$wfrSjzpfrSmyg ? v$rf;rkd; vkdr_ enf;AsL[m a=umif@ trsKd;om;’Drkdua&pD tzGJ@=uD; taeESif@ c&pf,mef ESif@rGwfqvifrsm;ukd vspfvsL&_xm;aom tajctaejzpfaeonf ?

              bmoma&; yËdyuQrsm;Y rnfonf@bufukdrsS jzefajzay;&ef / ndSEkdif;ay;&ef xdrf;xdrf;odrf;odrf;vkyf&ef r}uKd;pm;cJ@ ? Ekdif;iHa&;ESif@ bmoma&;a&maxG;&efrvkd[k qifajcay;onf ? trsKd;om;’Drkdua&pDtzGJ@u ‘Drkdu&pD&jyD;v#if vlrsKd;pkH bmompkH tm;vkH;.ta&;ukdaqmif&GufygrnfwJ@ ? ,ckzGif@ajymvkdufv#if Ak'<bmomvlxkESif@ bkef;awmf=uD;rsm;. axmufcHr_avsm@enf; oGm;rnfukd pkd;&drf[efwlonf ?

              ppfrSefaom ‘Drkdua&pDY vlrsm;pkonf vlenf;pkukd v$rf;rkd;tEkdifrusif@ovkd rjzpfap&ef vlrsm;pkonf vlenf;pk &ykdifcGif@rsm;ukd oabmxm;}uD; nSmwm umuG,fay;&ef wm0ef&Sdonf ?

            etz url&aomtcGif@ta&;ukdvufrv$wfbJ trsKd;om;’Drkdua&pDtzGJ@twGif; okd@ ukvm;rsm; xkd;azguf0ifa&mufaejyD[k 0g’jzef@csDr_pwifjyKvkyfae=ujyD ?

            ‘DEkdifiHa&;upm;uGuf trSwf(5) uawm@ ukdvkdeDacwfuxJu tm%m&Siftquf qufatmifjrifpGm usif@okH;cJ@wJ@ cGJjcm;&efwkdufay;jyD; tkyfcsKyfwJ@ vrf;pOfyg ? jrefrmEkdifiH om;tm;vkH; ‘DtuGufukd owdjyKrdoif@onf ?

            jrefrmhEkdifiHa&;twGuf taumif;qkH;EkdifiHa&;upm;uGuf ukd az:jyyg&ap ?

            vlxkw&yfvkH;ukd tajccHaom trsKd;om;’Drkdua&pDtzGJ@csKyf/ twkduftcH EkdifiHa&;ygwDrsm;tm;vkH; / wkdif;&if;om; vlrsKd;pktm;vkH;ESif@ bmoma&;tzGJ@rsm; tm;vkH; pnf;vkH;nDn$wfpGmjzihf pkaygif;I vuf&Sd etz ESif@nSdE_dif;jyD; tdrfapmif@tpkd;&w&yfzGJ@I jrefrmEkdifiHukd 5 ESpfrS 10 ESpf=umonftxd tkyfcsKyf&efyifjzpfonf ? wkdif;jynf bufpkH wkd;wufatmif&GufI / trsm;oabmwlEkdifrnf@ zGJ@pnf;ykHtajccH Oya’ wpfckukda&;qGJ&rnf ?

            &Spfav;vkH; v_kyf&Sm;r_rS tusKd;tjrwftcsKd@&cJ@aomfvnf; ukd;av;vkH; / ajcmuf

okH;vkH; ESif@ ygarmuQ qvkdif;oef;xGef; v_H@aqmfchJaom vlxkv_yf&Sm;r_rsm;rSm 0rf;enf;zG,f atmifjrifrSK ESifh a0;aecJ@ygonf ?

             ,cktcg oabmaumif;[efaqmif rsufESmcsKdjyD; oumavmif;aom pum;rsm;jzif@ urBmukd vSnf@zsm; aecJ@aom AkdvfcsKyfcifn$ef@ vnf;r&Sdawm@jyD jzpfI etz . [efaqmif rsufemzkH; uGmusovkdjzpfaejyD ? olwkd@.yifukd,f rsufESmukd wurBmvkH;u awhGjrifcJ@&jyD ?

             tmpD,H / tar&duef / Oa&mybkHaps;ESif@ ukvor*~ wkd@uvnf; ‘kdhtwkduftcHbuf rSm&SdaejyD ? ‘Dtcsdef[m u|Ekfyfwkd@ twkduftcHrsm; nDnDn$wfn$wfjzif@ usm;uGufa&G@cGif@&aom tvSnf@yg ?

·       tqdyfr&dSaomajrGqkdvsif uav;uyifrav;pm;wwfyg /

·       e*g;rSef;odatmif tarmuf axmifjy&ef tcsdefa&mufjyD ?

·       vlxktkH=uGr_rpEkdifao;cif t=urf;rzufaom tm%mzDqef r_rsm;ukdpwifoif@jyD ?

·       etz ppftpkd;&eSif@aqGrsKd;rdwfaqGrsm;ukd 0kdif;z,fa&Smif=uOf=upkd@ ?

·       ppftpkd;ESif@wwfEkdifor# ryufoufbJae=upkd@?

·       vkyf&Jol&Sdvsif etz xdyfykdif;ESif@aqGrsKd;rsm;ukd qef@usifr_jyKI tusKd;xdcdkufatmif vkyf&rnf ?

·       ,ck tcsdefY olwkd@wawG jrefrmEkdifiH twGif;Y vGwfvyfpGmoGm;vmv_yf&Sm;ae =uonf?

·       olwkd@wawGukdd ajzmufvSef@&efESif@ olwkd@v_yf&Sm;r_ukd xdrf;csKyfEkdif&efusKd;pm;&rnf ?

·       &Srf;acgif;aqmifrsm;ESif@ bm;rm;’kdif*suf(p) wkd@jyifqifaeaom EkdifiHwumw&m;&kH; Y etz ppfacgif;aqmifrsm;ukd w&m;pGJaom udpPukd 0kdif;0ef;ulnDvkyfaqmif=u&ef vkdjyD ?

·       tu,fI w&m;pGJEkdifjyD; EkdifiHwum &JtzGJ@rSzrf;0&rf;xkwffEkdifv#if olwkd@awGukd csKyfrdjyD ?

·       olwkd@rdwfaqG tdrfeD;em;jcif;EkdifiHrsm;okd@ oGm;&ef EkdifiHwumava=umif; xJ0if&efyifolwkd@@ ESpfcgjyefpOf;pm;&awm@rnf ?

·       olwkd@ESif@olwkd@rdom;pk aqGrsKd;rdwfaqGwk@d twGufpdwfrcsEdkif aomtajctaeukd a&mufap&rnf?

·       olwkd@ om;orD; rsm;EkdifiHjcm;Y pmoif&efta=umif;jyI ajcukyf,lr_rsm;ukdvnf; EkdifiHwum Oya’t& wm;jrpff=u&rnf ?

tao;pdwfukd etz rkef;wD;=uygpkd@ aqmif;yg;Y qufvufzwf&_yg&ef ?

(Akdvfatmif’ifa&;I xGef;atmifbmomjyefonf)