Tag Archives: control

Items of some interest:

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These are my recent Pin​board​.in links:

  • Pin­board: Book­mark Detail


    you-​​are-​​supposed-​​to-​​have-​​read-​​that-​​young-​​man

  • Cyber­net­ick Inkwell · On a def­i­n­i­tion of “open humanities”

    “The dig­i­tal human­i­ties are a part of the open human­i­ties to the extent that those same val­ues are held, though of course the purely dig­i­tal ele­ments (the code, the markup, the hard­ware) are unique to the dig­i­tal human­i­ties and live largely out­side of OH. That being said, much of DH—the com­mit­ment to open source, the col­lab­o­ra­tive nature of the field, the interdisciplinarity—is open.”

    open­ness digital-​​humanities the-​​inevitability-​​of-​​enclosures cultural-​​dynamics theory-​​as-​​code

  • Don’t Hold Your Breath | Paul Shep­heard | Archi­tect and writer | Words

    “…Nar­ra­tives are bet­ter than thumps, is the mes­sage; and in the field of human rela­tions this might well be so, but here’s the rub. Nature’s not a per­son. Nature’s not a mother. We are not fight­ing it but liv­ing it. The indus­trial land­scapes pur­sued with such ter­rific thor­ough­ness, the agri­cul­tural deserts as well as the sub­urbs, the mine­fields as well as the wind farms, the cities them­selves, are the out­comes not of rage but of sto­ries, nar­ra­tives in the dream of the human dom­i­na­tion of the world. That’s why I hug the boy’s head. It’s good that he sees him­self as a par­ti­cle of nature, a being rather than a human being, and his life as fun­da­men­tally con­sump­tive. He knows if he holds his breath he will die. He knows he must live in the present. So now I must try and teach him this: the bolt-​​ons and band-​​aids of the sus­tain­abil­ity move­ment that try to man­age our fear of the future are but another chap­ter in that book of dom­i­na­tion. It will not, in the face of the red giant, ulti­mately sus­tain. And nature as we know it now, in this snap­shot of human time, will not stay as it is, how­ever we try to pre­serve it.”

    paul-​​shepheard sus­tain­abil­ity crit­i­cism how-​​to-​​rite-​​gud

  • Grounds For Dis­per­sal | Paul Shep­heard | Archi­tect and writer | Words

    “Anonymity does not mean with­out deep con­tact, it means that the con­tact has no pre­empt­ing cer­e­mony. Col­lab­o­ra­tion, like­wise, is the proof of itself. It exists nei­ther before or after the moment it takes place, except in how it inflects your char­ac­ter. Inclu­sive­ness and par­tial­ity are sym­bi­otic, too. If par­tial is a move taken to out­flank hege­mony, the inclu­sive works to recom­bine dif­fer­ences. The para­doxes implicit in such terms are part of what makes them inter­est­ing. I’m try­ing to elu­ci­date a think­ing that is not dialec­tic, no longer depen­dent on oppo­si­tions, not look­ing for the right way. As one of the direc­tors of The­mepark, a Lon­don based fashion-​​architecture-​​photography-​​landscape com­bine said to me: “we are inter­ested in show­ing con­tent in its pure form.” At first I thought it was a joke, more of that London-​​Thing irony, but then I thought, what else is the mate­r­ial world but con­tent in its pure form? Today’s pho­tog­ra­phers, who mis­trust the Mag­num generation’s point-​​and-​​shoot real­i­ties, who set up every shot elab­o­rately, who treat land­scape, por­trait, action and spec­ta­cle as the same thing, are not being min­i­mal­ist. They are posit­ing the veloc­ity of the image.”

    paul-​​shepheard crit­i­cism style how-​​to-​​rite-​​gud

  • Mario Carpo: Post-​​Authorial Cre­ation | berfrois

    “This is where the design pro­fes­sions are increas­ingly feel­ing some dis­com­fort.  Design­ers like to design.  They like to be in charge of all aspects of what they cre­ate.  Many design­ers are noto­ri­ously con­trol freaks.  And rightly so: being in con­trol is their rai­son d’être.  Tra­di­tion­ally, design­ers “authored” objects and “autho­rized” their pro­duc­tion, repro­duc­tion, or mod­i­fi­ca­tion.  Their sig­na­ture had (it still has, by the way) bind­ing, legal value–implying autho­r­ial priv­i­leges pro­tected by law, and all the lia­bil­i­ties result­ing from that.  But once again, dig­i­tal tech­nolo­gies do not work that way.  When so many peo­ple can work together, who is in charge?  Who reaps the hon­ors?  Who pays the damages?”

    design con­trol planning-​​as-​​a-​​symptom mass-​​customization control-​​of-​​the-​​means-​​of-​​thought

  • Repub­li­can con­ser­vatism (com­plete rewrite) — Crooked Timber

    “The polit­i­cal impli­ca­tion, which has drawn some flak in the com­ments, but which I think is cor­rect is that there is no point in polit­i­cal engage­ment with author­i­tar­ian con­ser­v­a­tives. In a polit­i­cal envi­ron­ment where they are con­cen­trated in one party,politics is going to be a mat­ter the only strat­egy open to lib­er­als is to out­num­ber and out­vote them by peel­ing off as many periph­eral groups (for exam­ple, those who devi­ate from the approved cul­tural iden­tity in some way) as pos­si­ble. Obvi­ously, that’s an unpalat­able con­clu­sion in all sorts of ways, but I think it’s a valid one.”

    con­ser­vatism Repub­li­cans pol­i­tics nature-​​and-​​nurture-​​sittin-​​in-​​a-​​tree

  • Bot­tle the Infla­tion Mon­ster! — Crooked Timber

    ‘Fur­ther­more this seems to me to play once again into the view that ‘eco­nom­ics’ is tech­ni­cal and has right answers, while ‘pol­i­tics’ is emo­tive and con­tested, so stu­dents of the EU don’t have to talk about it.’

    eco­nom­ics infla­tion ped­a­gogy for-​​the-​​little-​​chilluns

Items of some interest…

Posted on by

These are my recent Pin​board​.in links:

  • [1105.4335] Phys­i­cal approaches to the dynam­ics of genetic cir­cuits: A tutorial

    “Cel­lu­lar behav­ior is gov­erned by gene reg­u­la­tory processes that are intrin­si­cally dynamic and non­lin­ear, and are sub­ject to non-​​negligible amounts of ran­dom fluc­tu­a­tions. Such con­di­tions are ubiq­ui­tous in phys­i­cal sys­tems, where they have been stud­ied for decades using the tools of sta­tis­ti­cal and non­lin­ear physics. The goal of this review is to show how approaches tra­di­tion­ally used in physics can help in reach­ing a systems-​​level under­stand­ing of liv­ing cells. To that end, we present an overview of the dynam­i­cal phe­nom­ena exhib­ited by genetic cir­cuits and their func­tional sig­nif­i­cance. We also describe the the­o­ret­i­cal and exper­i­men­tal approaches that are being used to unravel the rela­tion­ship between cir­cuit struc­ture and func­tion in dynam­i­cal cel­lu­lar processes under the influ­ence of noise, both at the single-​​cell level and in cel­lu­lar pop­u­la­tions, where inter­cel­lu­lar cou­pling plays an impor­tant role.”

    systems-​​biology biological-​​engineering genetic-​​regulatory-​​networks emergent-​​design bio­chem­istry overview

  • [1106.0371] A Novel Image Seg­men­ta­tion Enhance­ment Tech­nique based on Active Con­tour and Topo­log­i­cal Alignments

    “Topo­log­i­cal align­ments and snakes are used in image pro­cess­ing, par­tic­u­larly in locat­ing object bound­aries. Both of them have their own advan­tages and lim­i­ta­tions. To improve the over­all image bound­ary detec­tion sys­tem, we focused on devel­op­ing a novel algo­rithm for image pro­cess­ing. The algo­rithm we pro­pose to develop will based on the active con­tour method in con­junc­tion with topo­log­i­cal align­ments method to enhance the image detec­tion approach. The algo­rithm presents novel tech­nique to incor­po­rate the advan­tages of both Topo­log­i­cal Align­ments and snakes. Where the ini­tial seg­men­ta­tion by Topo­log­i­cal Align­ments is firstly trans­formed into the input of the snake model and begins its evolve­ment to the inter­ested object bound­ary. The results show that the algo­rithm can deal with low con­trast images and shape cells, demon­strate the seg­men­ta­tion accu­racy under weak image bound­aries, which respon­si­ble for lack­ing accu­racy in image detect­ing tech­niques. We have achieved bet­ter seg­men­ta­tion and bound­ary detect­ing for the image, also the abil­ity of the sys­tem to improve the low con­trast and deal with over and under segmentation.”

    image-​​segmentation algo­rithms nudge-​​targets

  • [1106.2508] A Prac­ti­cal Imple­men­ta­tion of the Bernoulli Factory

    “…While sev­eral prac­ti­cal uses of the method have been pro­posed in Monte Carlo appli­ca­tions, these require an imple­men­ta­tion frame­work that is flex­i­ble, gen­eral and effi­cient. We present such a frame­work for func­tions that are either strictly lin­ear, con­cave, or con­vex on the unit inter­val using a series of enve­lope func­tions defined through a cas­cade, and show that this method not only greatly reduces the num­ber of input bits needed in prac­tice com­pared to other cur­rently pro­posed solu­tions for more spe­cific prob­lems, but can eas­ily be cou­pled to more asymp­tot­i­cally effi­cient meth­ods to allow for the­o­ret­i­cally strong results.”

    algo­rithms numerical-​​methods Monte-​​Carlo-​​simulation probability-​​theory nudge-​​targets

  • [1105.1729] Evo­lu­tion­ary search for novel super­hard materials

    “We have devel­oped a method for pre­dic­tion of the hard­est crys­tal struc­tures in a given chem­i­cal sys­tem. It is based on the evo­lu­tion­ary algo­rithm USPEX and electronegativity-​​based hard­ness model that we have aug­mented with bond-​​valence model and graph the­ory. These exten­sions enable cor­rect descrip­tion of the hard­ness of lay­ered, mol­e­c­u­lar and low-​​symmetry crys­tal struc­tures. Apply­ing this method to C and TiO2, we have (i) obtained a num­ber of low-​​energy car­bon struc­tures with hard­ness slightly lower than dia­mond and (ii) proved that TiO2 in any of its pos­si­ble poly­morphs can­not be the hard­est oxide, its hard­ness being below 17 GPa.”

    materials-​​science genetic-​​algorithm condensed-​​matter sim­u­la­tion nudge-​​targets

  • [1109.0573] Phase Retrieval via Matrix Completion

    “This paper con­sid­ers the fun­da­men­tal prob­lem of recov­er­ing a gen­eral sig­nal, an image for exam­ple, from the mag­ni­tude of its Fourier trans­form. This prob­lem, also known as phase retrieval, arises in many appli­ca­tions and has chal­lenged engi­neers, physi­cists, and math­e­mati­cians for decades. Its ori­gin comes from the fact that detec­tors can often times only record the squared mod­u­lus of the Fres­nel or Fraun­hofer dif­frac­tion pat­tern of the radi­a­tion that is scat­tered from an object. In such set­tings, one can­not mea­sure the phase of the opti­cal wave reach­ing the detec­tor and, there­fore, much infor­ma­tion about the scat­tered object or the opti­cal field is lost since, as is well known, the phase encodes a lot of the struc­tural con­tent of the image we wish to form.”

    image-​​processing inverse-​​problems signal-​​processing system-​​identification frequency-​​space algo­rithms nudge-​​targets numerical-​​methods

  • [1109.0807] Har­monic Analy­sis of Boolean Net­works: Deter­mi­na­tive Power and Perturbations

    “Con­sider a large Boolean net­work with a feed for­ward struc­ture. Given a prob­a­bil­ity dis­tri­b­u­tion for the inputs, can one find-​​possibly small-​​collections of input nodes that deter­mine the states of most other nodes in the network?…”

    Boolean-​​networks Kauff­ma­nia com­plex­ol­ogy discrete-​​mathematics mathematical-​​recreations nudge-​​targets

  • [0801.0830] Evo­lu­tion of cen­tral pat­tern gen­er­a­tors for the con­trol of a five-​​link bipedal walk­ing mechanism

    “With the aim of pro­duc­ing a sta­ble human-​​like bipedal gait, a five-​​link pla­nar walk­ing mech­a­nism is cou­pled with a cen­tral pat­tern gen­er­a­tor (CPG) neural net­work, con­sist­ing of units based on Matsuoka’s half-​​center oscil­la­tor model with a firm basis in neu­ro­phys­i­ol­ogy. As a min­i­mal­is­tic approach to bipedal walk­ing, this type of walk­ing mech­a­nism con­tains only four actu­a­tors, and is lack­ing feet and ankles. The mech­a­nism is sim­u­lated with accu­rate physics, allow­ing real­is­tic fit­ness eval­u­a­tions for the cre­ation of CPG con­trollers through evo­lu­tion­ary com­pu­ta­tion. The oscil­la­tory para­me­ters, inter­nal con­nec­tiv­ity struc­ture, and exter­nal feed­back path­ways of the net­works are deter­mined through genetic algo­rithms (GA) opti­miza­tion. The evolved CPG net­works are trans­ferred to a hard­ware imple­men­ta­tion of the mech­a­nism, to test their per­for­mance under real-​​world dynam­ics. Results con­firm that the bio­log­i­cally inspired CPG model is very well suited for con­trol­ling legged loco­mo­tion, since a diverse man­i­fes­ta­tion of CPG net­works (with and with­out exter­nal feed­back) have been observed to suc­ceed dur­ing the course of GA eval­u­a­tions. Obser­va­tions also imply that while the CPG mech­a­nism is inher­ently able to sus­tain a sta­ble gait, the uti­liza­tion of feed­back path­ways makes the gait more human-​​like and is needed to pro­vide a means to adapt to irreg­u­lar­i­ties in the environment.”

    robot­ics engineering-​​design genetic-​​algorithm neural-​​networks cyber­net­ics nudge-​​targets

  • [1109.3351] Phys­i­cal lim­its on coop­er­a­tive protein-​​DNA bind­ing and the kinet­ics of com­bi­na­to­r­ial tran­scrip­tion regulation

    “Much of the com­plex­ity observed in gene reg­u­la­tion orig­i­nates from coop­er­a­tive protein-​​DNA bind­ing. While stud­ies of the tar­get search of pro­teins for their spe­cific bind­ing sites on the DNA have revealed design prin­ci­ples for the quan­ti­ta­tive char­ac­ter­is­tics of protein-​​DNA inter­ac­tions, no such prin­ci­ples are known for the coop­er­a­tive inter­ac­tions between DNA-​​binding pro­teins. We con­sider a sim­ple the­o­ret­i­cal model for two inter­act­ing tran­scrip­tion fac­tor (TF) species, search­ing for and bind­ing to two adja­cent tar­get sites hid­den in the genomic back­ground. We study the kinetic com­pe­ti­tion of a dimer search path­way and a monomer search path­way, as well as the steady-​​state reg­u­la­tion func­tion medi­ated by the two TFs over a broad range of TF-​​TF inter­ac­tion strengths. Using a tran­scrip­tional AND-​​logic as exem­plary func­tional con­text, we iden­tify the func­tion­ally desir­able regime for the inter­ac­tion. We find that both weak and very strong TF-​​TF inter­ac­tions are favor­able, albeit with dif­fer­ent char­ac­ter­is­tics. How­ever, there is also an unfa­vor­able regime of inter­me­di­ate inter­ac­tions where the genetic response is pro­hib­i­tively slow.”

    biological-​​engineering genetic-​​regularory-​​networks systems-​​biology emergent-​​design nudge-​​targets

  • [1109.6874] #h00t: Cen­sor­ship Resis­tant Microblogging

    “Microblog­ging ser­vices such as Twit­ter are an increas­ingly impor­tant way to com­mu­ni­cate, both for indi­vid­u­als and for groups through the use of hash­tags that denote top­ics of con­ver­sa­tion. How­ever, groups can be eas­ily blocked from com­mu­ni­cat­ing through block­ing of posts with the given hash­tags. We pro­pose #h00t, a sys­tem for cen­sor­ship resis­tant microblog­ging. #h00t presents an inter­face that is much like Twit­ter, except that hash­tags are replaced with very short hashes (e.g., 24 bits) of the group iden­ti­fier. Nat­u­rally, with such short hashes, hash­tags from dif­fer­ent groups may col­lide and #h00t users will actu­ally seek to cre­ate col­li­sions. By encrypt­ing all posts with keys derived from the group iden­ti­fiers, #h00t client soft­ware can fil­ter out other groups’ posts while mak­ing such fil­ter­ing dif­fi­cult for the adver­sary. In essence, by lever­ag­ing col­li­sions, groups can tun­nel their posts in other groups’ posts. A cen­sor could not block a given group with­out also block­ing the other groups with col­lid­ing hash­tags. We eval­u­ate the fea­si­bil­ity of #h00t through traces col­lected from Twit­ter, show­ing that a sin­gle mod­ern com­puter has enough com­pu­ta­tional through­put to encrypt every tweet sent through Twit­ter in real time. We also use these traces to ana­lyze the band­width and anonymity trade­offs that would come with dif­fer­ent vari­a­tions on how group iden­ti­fiers are encoded and hash­tags are selected to pur­pose­fully col­lide with one another.”

    social-​​media steganog­ra­phy robust­ness activism cute

  • [1107.0414] A ran­dom walk on image patches

    “In this paper we address the prob­lem of under­stand­ing the suc­cess of algo­rithms that orga­nize patches accord­ing to graph-​​based met­rics. Algo­rithms that ana­lyze patches extracted from images or time series have led to state-​​of-​​the art tech­niques for clas­si­fi­ca­tion, denois­ing, and the study of non­lin­ear dynam­ics. The main con­tri­bu­tion of this work is to pro­vide a the­o­ret­i­cal expla­na­tion for the above exper­i­men­tal obser­va­tions. Our approach relies on a detailed analy­sis of the com­mute time met­ric on pro­to­typ­i­cal graph mod­els that epit­o­mize the geom­e­try observed in gen­eral patch graphs.…”

    image-​​segmentation image-​​analysis algo­rithms com­bi­na­torics nudge-​​targets

  • [1107.0385] An algo­rithm for autonomously plot­ting solu­tion sets in the pres­ence of turn­ing points

    “Plot­ting solu­tion sets for par­tic­u­lar equa­tions may be com­pli­cated by the exis­tence of turn­ing points. Here we describe an algo­rithm which not only over­comes such prob­lem­atic points, but does so in the most gen­eral of set­tings. Appli­ca­tions of the algo­rithm are high­lighted through two exam­ples: the first pro­vides ver­i­fi­ca­tion, while the sec­ond demon­strates a non-​​trivial appli­ca­tion. The lat­ter is fol­lowed by a thor­ough run-​​time analy­sis. While both exam­ples deal with bivari­ate equa­tions, it is dis­cussed how the algo­rithm may be gen­er­al­ized for space curves in $R^{3}$.”

    visu­al­iza­tion math­e­mat­ics graph­ics approx­i­ma­tion algo­rithms nudge-​​targets

  • [1105.1033] Adap­tively Learn­ing the Crowd Kernel

    “We intro­duce an algo­rithm that, given n objects, learns a sim­i­lar­ity matrix over all n^2 pairs, from crowd­sourced data alone. The algo­rithm sam­ples responses to adap­tively cho­sen triplet-​​based relative-​​similarity queries. Each query has the form “is object ‘a’ more sim­i­lar to ‘b’ or to ‘c’?” and is cho­sen to be max­i­mally infor­ma­tive given the pre­ced­ing responses. The out­put is an embed­ding of the objects into Euclid­ean space (like MDS); we refer to this as the “crowd ker­nel.” SVMs reveal that the crowd ker­nel cap­tures promi­nent and sub­tle fea­tures across a num­ber of domains, such as “is striped” among neck­ties and “vowel vs. con­so­nant” among letters.”

    clas­si­fi­ca­tion ontology-​​discovery crowd­sourc­ing feature-​​extraction algo­rithms nudge-​​targets performance-​​space-​​analysis

  • [1109.1030] An Algo­rithm for Detect­ing Intrin­si­cally Knot­ted Graphs

    “We describe an algo­rithm that rec­og­nizes some (per­haps all) intrin­si­cally knot­ted (IK) graphs, and can help find knot­less embed­dings for graphs that are not IK. The algo­rithm, imple­mented as a Math­e­mat­ica pro­gram, has already been used by Gold­berg, Mattman, and Naimi [6] to greatly expand the list of known minor min­i­mal IK graphs, and to find knot­less embed­dings for some graphs that had pre­vi­ously resisted attempts to clas­sify them as IK or non-​​IK.”

    com­bi­na­torics topol­ogy algo­rithms nudge-​​targets

  • [1109.5635] Approx­i­mat­ing Edit Dis­tance in Near-​​Linear Time

    “We show how to com­pute the edit dis­tance between two strings of length n up to a fac­tor of 2^{~O(sqrt(log n))} in n^(1+o(1)) time. This is the first sub-​​polynomial approx­i­ma­tion algo­rithm for this prob­lem that runs in near-​​linear time, improv­ing on the state-​​of-​​the-​​art n^(1/3+o(1)) approx­i­ma­tion. Pre­vi­ously, approx­i­ma­tion of 2^{~O(sqrt(log n))} was known only for embed­ding edit dis­tance into l_​1, and it is not known if that embed­ding can be com­puted in less than qua­dratic time.”

    algo­rithms string-​​editing Levenshtein-​​distance rewriting-​​systems bioin­for­mat­ics nudge-​​targets

  • [1107.1866] Priority-​​based task reas­sign­ments in hier­ar­chi­cal 2D mesh-​​connected sys­tems using tableaux

    “Task reas­sign­ments in 2D mesh-​​connected sys­tems (2D-​​MSs) have been researched and sim­u­lated for sev­eral decades. We pro­pose a hier­ar­chi­cal 2D mesh-​​connected sys­tem (2D-​​HMS) in order to exploit the reg­u­lar nature of a 2D-​​MS. In our approach priority-​​based task assign­ments and reas­sign­ments in a 2D-​​HMS are rep­re­sented by tableaux and their algo­rithms. We pro­vide exam­ples of priority-​​based task reas­sign­ments in a 2D-​​HMS in which task relo­ca­tions are sim­ply reduced to a jeu de taquin slide.”

    sched­ul­ing operations-​​research algo­rithms grid-​​computing opti­miza­tion nudge-​​targets

  • [1101.4744] Clus­ter­ing func­tional data using wavelets

    “We present two meth­ods for detect­ing pat­terns and clus­ters in high dimen­sional time-​​dependent func­tional data. Our meth­ods are based on wavelet-​​based sim­i­lar­ity mea­sures, since wavelets are well suited for iden­ti­fy­ing highly dis­crim­i­nant local time and scale fea­tures. The mul­tires­o­lu­tion aspect of the wavelet trans­form pro­vides a time-​​scale decom­po­si­tion of the sig­nals allow­ing to visu­al­ize and to clus­ter the func­tional data into homo­ge­neous groups. For each input func­tion, through its empir­i­cal orthog­o­nal wavelet trans­form the first method uses the dis­tri­b­u­tion of energy across scales gen­er­ate a handy num­ber of fea­tures that can be suf­fi­cient to still make the sig­nals well dis­tin­guish­able. Our new sim­i­lar­ity mea­sure com­bined with an effi­cient fea­ture selec­tion tech­nique in the wavelet domain is then used within more or less clas­si­cal clus­ter­ing algo­rithms to effec­tively dif­fer­en­ti­ate among high dimen­sional pop­u­la­tions. The sec­ond method uses dis­sim­i­lar­ity mea­sures between the whole time-​​scale rep­re­sen­ta­tions and are based on wavelet-​​coherence tools. The clus­ter­ing is then per­formed using a k-​​centroid algo­rithm start­ing from these dis­sim­i­lar­i­ties. Prac­ti­cal per­for­mance of these meth­ods that jointly designs both the fea­ture selec­tion in the wavelet domain and the clas­si­fi­ca­tion dis­tance is demon­strated through sim­u­la­tions as well as daily pro­files of the French elec­tric­ity power demand.”

    clas­si­fi­ca­tion time-​​series feature-​​extraction machine-​​learning multiobjective-​​optimization ontology-​​discovery wavelets nudge-​​targets

  • [1105.3726] Con­trol­ling Com­plex Net­works with Com­pen­satory Perturbations

    “The response of com­plex net­works to per­tur­ba­tions is of utmost impor­tance in areas as diverse as ecosys­tem man­age­ment, emer­gency response, and cell repro­gram­ming. A fun­da­men­tal prop­erty of net­works is that the per­tur­ba­tion of one node can affect other nodes, in a process that may cause the entire or sub­stan­tial part of the sys­tem to change behav­ior and pos­si­bly col­lapse. Recent research in meta­bolic and food-​​web net­works has demon­strated the con­cept that net­work dam­age caused by exter­nal per­tur­ba­tions can often be mit­i­gated or reversed by the appli­ca­tion of com­pen­satory per­tur­ba­tions. Com­pen­satory per­tur­ba­tions are con­strained to be phys­i­cally admis­si­ble and amenable to imple­men­ta­tion on the net­work. How­ever, the sys­tem­atic iden­ti­fi­ca­tion of com­pen­satory per­tur­ba­tions that con­form to these con­straints remains an open prob­lem. Here, we present a method to con­struct com­pen­satory per­tur­ba­tions that can con­trol the fate of gen­eral net­works under such con­straints. Our approach accounts for the full non­lin­ear behav­ior of real com­plex net­works and can bring the sys­tem to a desir­able tar­get state even when this state is not directly acces­si­ble. Appli­ca­tions to genetic net­works show that com­pen­satory per­tur­ba­tions are effec­tive even when lim­ited to a small frac­tion of all nodes in the net­work and that they are far more effec­tive when lim­ited to the highest-​​degree nodes. The approach is con­cep­tu­ally sim­ple and com­pu­ta­tion­ally effi­cient, mak­ing it suit­able for the res­cue, con­trol, and repro­gram­ming of large com­plex net­works in var­i­ous domains.”

    emergent-​​design com­plex­ol­ogy con­trol biological-​​engineering nudge-​​targets

  • [1109.1275] A For­mal Ver­i­fi­ca­tion Approach to the Design of Syn­thetic Gene Networks

    “The design of genetic net­works with spe­cific func­tions is one of the major goals of syn­thetic biol­ogy. How­ever, con­struct­ing bio­log­i­cal devices that work “as required” remains chal­leng­ing, while the cost of uncov­er­ing flawed designs exper­i­men­tally is large. To address this issue, we pro­pose a fully auto­mated frame­work that allows the cor­rect­ness of syn­thetic gene net­works to be for­mally ver­i­fied in sil­ico from rich, high level func­tional spec­i­fi­ca­tions. Given a device, we auto­mat­i­cally con­struct a math­e­mat­i­cal model from exper­i­men­tal data char­ac­ter­iz­ing the parts it is com­posed of. The spe­cific model struc­ture guar­an­tees that all exper­i­men­tal obser­va­tions are cap­tured and allows us to con­struct finite abstrac­tions through poly­he­dral oper­a­tions. The cor­rect­ness of the model with respect to tem­po­ral logic spec­i­fi­ca­tions can then be ver­i­fied auto­mat­i­cally using meth­ods inspired by model check­ing. Over­all, our pro­ce­dure is con­ser­v­a­tive but it can fil­ter through a large num­ber of poten­tial device designs and select few that sat­isfy the spec­i­fi­ca­tion to be imple­mented and tested fur­ther exper­i­men­tally. Illus­tra­tive exam­ples of the appli­ca­tion of our meth­ods to the design of sim­ple syn­thetic gene net­works are included.”

    genetic-​​regulatory-​​networks bioin­for­mat­ics biological-​​engineering design-​​automation emergent-​​design acceptance-​​testing performance-​​measure nudge

  • [1108.1150] Epis­ta­sis can lead to frag­mented neu­tral spaces and con­tin­gency in evolution

    “Under neu­tral rec­i­p­ro­cal sign epis­ta­sis, two genetic changes are jointly neu­tral, even though their indi­vid­ual effects are dele­te­ri­ous. By using the widely stud­ied map­ping from an RNA sequence to sec­ondary struc­ture, we inves­ti­gate the effect of this kind of epis­ta­sis on neu­tral spaces cor­re­spond­ing to net­works of geno­types that fold to the same sec­ondary struc­ture. Neu­tral net­works for RNA struc­tures with n bonds are typ­i­cally frag­mented into at least 2n dif­fer­ent neu­tral com­po­nents that can­not be con­nected by sin­gle point muta­tions. By exhaus­tive enu­mer­a­tion of all RNA sec­ondary struc­tures of sequences of length 15 we show that most net­works are not dom­i­nated by one neu­tral com­po­nent, but are rather bro­ken up into mul­ti­ple large com­po­nents. Although they gen­er­ate the same phe­no­type, com­po­nents of a sin­gle neu­tral net­work are het­ero­ge­neous, show­ing wide vari­a­tions in their robust­ness and their evolv­abil­ity. Both prop­er­ties are cor­re­lated with com­po­nent size, rather than with the size of their under­ly­ing neu­tral net­work. In par­tic­u­lar, sets of acces­si­ble phe­no­types can vary quite strongly between com­po­nents. Thus, the poten­tial for future inno­va­tion is con­tin­gent on which neu­tral com­po­nent a pop­u­la­tion occu­pies. We fur­ther argue that neu­tral rec­i­p­ro­cal sign epis­ta­sis may have sim­i­lar con­se­quences for neu­tral evo­lu­tion of other bio­log­i­cal sys­tems as well.”

    com­bi­na­torics RNA neutral-​​networks com­plex­ol­ogy bioin­for­mat­ics polymer-​​models mathematical-​​recreations nudge-​​targets

  • Old​Fonts​.com | About Us

    “Will­son founded 3IP in 1989 to self-​​publish a book of pre­ten­tious nature essays. Soon after, he found him­self tin­ker­ing with type design, and 3IP has since become known for its library of authentic-​​looking hand­writ­ing fonts—many of them mod­eled after his­tor­i­cal penmanship—and antique text simulations.”

    typog­ra­phy fonts hand­writ­ing

  • Col­lec­tive Wis­dom — Crooked Timber

    “More broadly, a sim­ple dic­tum such as ‘lis­ten to the experts’ isn’t going to work, pre­cisely because our most pow­er­ful meth­ods of gen­er­at­ing new knowl­edge (viz. the sci­ences) are not so much based on lis­ten­ing to indi­vid­ual experts, as on includ­ing these experts (and many oth­ers) in broader social sys­tems which expose them con­tin­u­ally to the ideas of oth­ers and vice-​​versa. Design­ing (or – per­haps bet­ter– nur­tur­ing) such sys­tems is hard to think about and hard to do – but it has to be the way forward.”

    via:arsyed wisdom-​​of-​​crowds com­plex­ol­ogy inno­va­tion cultural-​​assumptions cre­den­tial­ing problem-​​solving what-​​is-​​true-​​is-​​what-​​gets-​​said

  • [1109.1146] A Dis­trib­uted Mincut/​Maxflow Algo­rithm Com­bin­ing Path Aug­men­ta­tion and Push-​​Relabel

    “We develop a novel dis­trib­uted algo­rithm for the min­i­mum cut prob­lem. We pri­mar­ily aim at solv­ing large sparse prob­lems. Assum­ing ver­tices of the graph are par­ti­tioned into sev­eral regions, the algo­rithm per­forms path aug­men­ta­tions inside the regions and updates of the push-​​relabel style between the regions. The inter­ac­tion between regions is con­sid­ered expen­sive (regions are loaded into the mem­ory one-​​by-​​one or located on sep­a­rate machines in a net­work). The algo­rithm works in sweeps — passes over all regions. Let $B$ be the set of ver­tices inci­dent to inter-​​region edges of the graph. We present a sequen­tial and par­al­lel ver­sions of the algo­rithm which ter­mi­nate in at most $2|B|^2+1$ sweeps. The com­pet­ing algo­rithm by Delong and Boykov uses push-​​relabel updates inside regions. In the case of a fixed par­ti­tion we prove that this algo­rithm has a tight $O(n^2)$ bound on the num­ber of sweeps, where $n$ is the num­ber of ver­tices. We tested sequen­tial ver­sions of the algo­rithms on instances of maxflow prob­lems in com­puter vision. Exper­i­men­tally, the num­ber of sweeps required by the new algo­rithm is much lower than for the Delong and Boykov’s vari­ant. Large prob­lems (up to $108$ ver­tices and $6cdot 108$ edges) are solved using under 1GB of mem­ory in about 10 sweeps.”

    algo­rithms operations-​​research nudge-​​targets

  • [1105.4953] A fast near­est neigh­bor search algo­rithm based on vec­tor quantization

    “In this arti­cle, we pro­pose a new fast near­est neigh­bor search algo­rithm, based on vec­tor quan­ti­za­tion. Like many other branch and bound search algo­rithms [1,10], a pre­pro­cess­ing recur­sively par­ti­tions the data set into dis­jointed sub­sets until the num­ber of points in each part is small enough. In doing so, a search-​​tree data struc­ture is built. This pre­lim­i­nary recur­sive data-​​set par­ti­tion is based on the vec­tor quan­ti­za­tion of the empir­i­cal dis­tri­b­u­tion of the ini­tial data-​​set. Unlike pre­vi­ously cited meth­ods, this kind of par­ti­tions does not a pri­ori allow to elim­i­nate sev­eral brother nodes in the search tree with a sin­gle test. To over­come this dif­fi­culty, we pro­pose an algo­rithm to reduce the num­ber of tested brother nodes to a min­i­mal list that we call “friend Voronoi cells”. The com­plete descrip­tion of the method requires a deeper insight into the prop­er­ties of Delau­nay tri­an­gu­la­tions and Voronoi diagrams”

    algo­rithms search-​​algorithms data-​​analysis nudge-​​targets

  • [1108.0986] A prox­i­mal point algo­rithm for sequen­tial fea­ture extrac­tion applications

    “We pro­pose a prox­i­mal point algo­rithm to solve LAROS prob­lem, that is the prob­lem of find­ing a “large approx­i­mately rank-​​one sub­ma­trix”. This LAROS prob­lem is used to sequen­tially extract fea­tures in data. We also develop a new stop­ping cri­te­rion for the prox­i­mal point algo­rithm, which is based on the dual­ity con­di­tions of eps-​​optimal solu­tions of the LAROS prob­lem, with a the­o­ret­i­cal guar­an­tee. We test our algo­rithm with two image data­bases and show that we can use the LAROS prob­lem to extract appro­pri­ate com­mon fea­tures from these images.”

    algo­rithms image-​​segmentation feature-​​extraction nudge-​​targets

  • [1011.2348] Ergodic Con­trol and Poly­he­dral approaches to PageR­ank Optimization

    “We study a gen­eral class of PageR­ank opti­miza­tion prob­lems which con­sist in find­ing an opti­mal out­link strat­egy for a web site sub­ject to design con­straints. We con­sider both a con­tin­u­ous prob­lem, in which one can choose the inten­sity of a link, and a dis­crete one, in which in each page, there are oblig­a­tory links, fac­ul­ta­tive links and for­bid­den links. We show that the con­tin­u­ous prob­lem, as well as its dis­crete vari­ant when there are no con­straints cou­pling dif­fer­ent pages, can both be mod­eled by con­strained Markov deci­sion processes with ergodic reward, in which the web­mas­ter deter­mines the tran­si­tion prob­a­bil­i­ties of web­surfers. Although the num­ber of actions turns out to be expo­nen­tial, we show that an asso­ci­ated poly­tope of tran­si­tion mea­sures has a con­cise rep­re­sen­ta­tion, from which we deduce that the con­tin­u­ous prob­lem is solv­able in poly­no­mial time, and that the same is true for the dis­crete prob­lem when there are no cou­pling con­straints. We also pro­vide effi­cient algo­rithms, adapted to very large net­works. Then, we inves­ti­gate the qual­i­ta­tive fea­tures of opti­mal out­link strate­gies, and iden­tify in par­tic­u­lar assump­tions under which there exists a “mas­ter” page to which all con­trolled pages should point. We report numer­i­cal results on frag­ments of the real web graph.”

    opti­miza­tion PageR­ank operations-​​research algo­rithms nudge-​​targets

Items of some interest…

Posted on by

These are my recent Pin​board​.in links:

  • [1106.1804] A Crit­i­cal Assess­ment of Bench­mark Com­par­i­son in Planning

    “Recent trends in plan­ning research have led to empir­i­cal com­par­i­son becom­ing com­mon­place. The field has started to set­tle into a method­ol­ogy for such com­par­isons, which for obvi­ous prac­ti­cal rea­sons requires run­ning a sub­set of plan­ners on a sub­set of prob­lems. In this paper, we char­ac­ter­ize the method­ol­ogy and exam­ine eight implicit assump­tions about the prob­lems, plan­ners and met­rics used in many of these com­par­isons. The prob­lem assump­tions are: PR1) the per­for­mance of a gen­eral pur­pose plan­ner should not be penalized/​biased if exe­cuted on a sam­pling of prob­lems and domains, PR2) minor syn­tac­tic dif­fer­ences in rep­re­sen­ta­tion do not affect per­for­mance, and PR3) prob­lems should be solv­able by STRIPS capa­ble plan­ners unless they require ADL. The plan­ner assump­tions are: PL1) the lat­est ver­sion of a plan­ner is the best one to use, PL2) default para­me­ter set­tings approx­i­mate good per­for­mance, and PL3) time cut-​​offs do not unduly bias out­come. The met­rics assump­tions are: M1) per­for­mance degrades sim­i­larly for each plan­ner when run on degraded run­time envi­ron­ments (e.g., machine plat­form) and M2) the num­ber of plan steps dis­tin­guishes per­for­mance. We find that most of these assump­tions are not sup­ported empir­i­cally; in par­tic­u­lar, that plan­ners are affected dif­fer­ently by these assump­tions. We con­clude with a call to the com­mu­nity to devote research resources to improv­ing the state of the prac­tice and espe­cially to enhanc­ing the avail­able bench­mark problems.”

    plan­ning bench­mark­ing algo­rithms horse-​​races engineering-​​design operations-​​research nudge-​​targets

  • [1108.4361] The rela­tion­ship between acquain­tance­ship and coau­thor­ship in sci­en­tific col­lab­o­ra­tion networks

    “This arti­cle exam­ines the rela­tion­ship between acquain­tance­ship and coau­thor­ship pat­terns in a multi-​​disciplinary, multi-​​institutional, geo­graph­i­cally dis­trib­uted research cen­ter. Two social net­works are con­structed and com­pared: a net­work of coau­thor­ship, rep­re­sent­ing how researchers write arti­cles with one another, and a net­work of acquain­tance­ship, rep­re­sent­ing how those researchers know each other on a per­sonal level, based on their responses to an online sur­vey. Sta­tis­ti­cal analy­ses of the topol­ogy and com­mu­nity struc­ture of these net­works point to the impor­tance of small-​​scale, local, per­sonal net­works pred­i­cated upon acquain­tance­ship for accom­plish­ing col­lab­o­ra­tive work in sci­en­tific communities.”

    academic-​​culture network-​​theory cita­tion social-​​networks

  • [1108.4223] The set-​​theoretic multiverse

    “The mul­ti­verse view in set the­ory, intro­duced and argued for in this arti­cle, is the view that there are many dis­tinct con­cepts of set, each instan­ti­ated in a cor­re­spond­ing set-​​theoretic uni­verse. The uni­verse view, in con­trast, asserts that there is an absolute back­ground set con­cept, with a cor­re­spond­ing absolute set-​​theoretic uni­verse in which every set-​​theoretic ques­tion has a def­i­nite answer. The mul­ti­verse posi­tion, I argue, explains our expe­ri­ence with the enor­mous diver­sity of set-​​theoretic pos­si­bil­i­ties, a phe­nom­e­non that chal­lenges the uni­verse view. In par­tic­u­lar, I argue that the con­tin­uum hypoth­e­sis is set­tled on the mul­ti­verse view by our exten­sive knowl­edge about how it behaves in the mul­ti­verse, and as a result it can no longer be set­tled in the man­ner for­merly hoped for.”

    math­e­mat­ics mathematical-​​criticism looking-​​forward-​​to-​​understanding-​​this-​​someday pragmatism-it-ain’t

  • [1102.1934] The struc­ture of the Arts & Human­i­ties Cita­tion Index: A map­ping on the basis of aggre­gated cita­tions among 1,157 journals

    “Using the Arts & Human­i­ties Cita­tion Index (A&HCI) 2008, we apply map­ping tech­niques pre­vi­ously devel­oped for map­ping jour­nal struc­tures in the Sci­ence and Social Sci­ence Cita­tion Indices. Cita­tion rela­tions among the 110,718 records were aggre­gated at the level of 1,157 jour­nals spe­cific to the A&HCI, and the jour­nal struc­tures are ques­tioned on whether a cog­ni­tive struc­ture can be recon­structed and visu­al­ized. Both cosine-​​normalization (bot­tom up) and fac­tor analy­sis (top down) sug­gest a divi­sion into approx­i­mately twelve sub­sets. The rela­tions among these sub­sets are explored using var­i­ous visu­al­iza­tion tech­niques. How­ever, we were not able to retrieve this struc­ture using the ISI Sub­ject Cat­e­gories, includ­ing the 25 cat­e­gories which are spe­cific to the A&HCI. We dis­cuss options for val­i­da­tion such as against the cat­e­gories of the Human­i­ties Indi­ca­tors of the Amer­i­can Acad­emy of Arts and Sci­ences, the panel struc­ture of the Euro­pean Ref­er­ence Index for the Human­i­ties (ERIH), and com­pare our results with the cur­ricu­lum orga­ni­za­tion of the Human­i­ties Sec­tion of the Col­lege of Let­ters and Sci­ences of UCLA as an exam­ple of insti­tu­tional organization.”

    network-​​theory citation-​​networks human­i­ties academic-​​culture quantitative-​​humanities

  • [1108.4220] A Dynam­i­cal Sys­tems Approach for Sta­tic Eval­u­a­tion in Go

    “In the paper argu­ments are given why the con­cept of sta­tic eval­u­a­tion has the poten­tial to be a use­ful exten­sion to Monte Carlo tree search. A new con­cept of mod­el­ing sta­tic eval­u­a­tion through a dynam­i­cal sys­tem is intro­duced and strengths and weak­nesses are dis­cussed. The gen­eral suit­abil­ity of this approach is demonstrated.”

    representation-​​theory plan­ning monte-​​carlo-​​models nudge algo­rithms

  • [1105.5449] AntNet: Dis­trib­uted Stig­mer­getic Con­trol for Com­mu­ni­ca­tions Networks

    “…We com­pare our algo­rithm with six state-​​of-​​the-​​art rout­ing algo­rithms com­ing from the telecom­mu­ni­ca­tions and machine learn­ing fields. The algo­rithms’ per­for­mance is eval­u­ated over a set of real­is­tic test­beds. We run many exper­i­ments over real and arti­fi­cial IP data­gram net­works with increas­ing num­ber of nodes and under sev­eral par­a­dig­matic spa­tial and tem­po­ral traf­fic dis­tri­b­u­tions. Results are very encour­ag­ing. AntNet showed supe­rior per­for­mance under all the exper­i­men­tal con­di­tions with respect to its com­peti­tors. We ana­lyze the main char­ac­ter­is­tics of the algo­rithm and try to explain the rea­sons for its superiority.”

    ant-​​colony-​​optimization network-​​theory net­works con­trol algo­rithms nudge-​​targets rout­ing

  • Bozo Sapi­ens: Sacco and Vanzetti: Evidence

    “Wigmore’s tech­nique, like prob­a­bil­ity itself, is both wide-​​ranging and tediously painstak­ing; his book was pop­u­lar only among insom­niac judges. But now that com­put­ers can take on the numer­i­cal drudgery, it is prov­ing its worth in just such tan­gled cases as Sacco’s and Vanzetti’s. The legal schol­ars Joseph Kadane and David Schum have applied a sophis­ti­cated exten­sion of Wigmore’s method to the vast body of evi­dence from the case. Theirs is a remark­able achieve­ment; their charts retain all the orig­i­nal com­plex­i­ties: the facts with­held or per­verted, the hearsay, the lies told and dis­avowed on both sides, the charged polit­i­cal atmos­phere of eighty years ago. They never dis­count a fact, no mat­ter how far-​​fetched; they  sim­ply give it its due weight in their dynamic struc­ture. Their con­clu­sion?  Unjust though it is to sum­ma­rize a book in a sen­tence, the bal­ance of prob­a­bil­ity seems to favor the view expressed long ago by one of the defen­dants’ close com­pan­ions: “every­one in the Boston anar­chis­tic cir­cle knew that Sacco was guilty and that Vanzetti was inno­cent as far as the actual par­tic­i­pa­tion in the killing.” So, there it is: whichever side our polit­i­cal instincts favor, we are des­tined to be half wrong. Vanzetti’s last words were: “I wish to for­give some peo­ple for what they are now doing to me.”  If we were all will­ing to make the extra effort to work out the prob­a­bil­i­ties, per­haps we might not need for­give­ness so often.”

    probability-​​theory legal-​​studies computational-​​methods his­tory

  • Get­ting first sale wrong

    “I hate to imag­ine it, but this deci­sion raises some fright­en­ing pos­si­bil­i­ties and requires greater vig­i­lance on the part of librar­i­ans.  At the very least, libraries must demand infor­ma­tion from pub­lish­ers about where every item has been man­u­fac­tured. Obtain­ing such infor­ma­tion is no longer an option, since our legal uses of the things we buy now depends on know­ing this, and the place where the pub­lisher is located or where the sale took place is sim­ply not suf­fi­cient.  But what I really fear is that pub­lish­ers will begin to man­u­fac­ture more of their works over­seas and then try to demand a higher price – one that includes “pub­lic lend­ing rights” – from libraries. If libraries are in a dif­fi­cult posi­tion, stu­dents may be even worse off under the Sec­ond Circuit’s rul­ing.  Again, pub­lish­ers now have an incen­tive to man­u­fac­ture their text­books abroad and sell them to U.S. stu­dents.  Such stu­dents would no longer have the right to re-​​sell their text­books or to pur­chase used texts.  The defen­dant in the case, Supap Kirt­saeng, had made a lucra­tive busi­ness out of reselling text­books pur­chased in Asia.  He was per­haps an unsym­pa­thetic party, but what he was doing was not dif­fer­ent in kind from the resale of texts that is com­mon on all col­lege cam­puses.  This activ­ity makes higher edu­ca­tion a lit­tle more pos­si­ble for many.  Now pub­lish­ers have an easy way for to close down this sec­ondary mar­ket for text­books, about which they have com­plained for years.  In the process, the cost of edu­ca­tion for col­lege stu­dents would be pushed up even further.”

    copy­right insan­ity intellectual-​​property academic-​​culture librar­i­ans

  • [1106.6037] Black Hole Search with Finite Automata Scat­tered in a Syn­chro­nous Torus

    “We con­sider the prob­lem of locat­ing a black hole in syn­chro­nous anony­mous net­works using finite state agents. A black hole is a harm­ful node in the net­work that destroys any agent vis­it­ing that node with­out leav­ing any trace. The objec­tive is to locate the black hole with­out destroy­ing too many agents. This is dif­fi­cult to achieve when the agents are ini­tially scat­tered in the net­work and are unaware of the loca­tion of each other. Pre­vi­ous stud­ies for black hole search used more pow­er­ful mod­els where the agents had non-​​constant mem­ory, were labelled with dis­tinct iden­ti­fiers and could either write mes­sages on the nodes of the net­work or mark the edges of the net­work. In con­trast, we solve the prob­lem using a small team of finite-​​state agents each car­ry­ing a con­stant num­ber of iden­ti­cal tokens that could be placed on the nodes of the net­work. Thus, all resources used in our algo­rithms are inde­pen­dent of the net­work size. We restrict our atten­tion to ori­ented torus net­works and first show that no finite team of finite state agents can solve the prob­lem in such net­works, when the tokens are not mov­able. In case the agents are equipped with mov­able tokens, we deter­mine lower bounds on the num­ber of agents and tokens required for solv­ing the prob­lem in torus net­works of arbi­trary size. Fur­ther, we present a deter­min­is­tic solu­tion to the black hole search prob­lem for ori­ented torus net­works, using the min­i­mum num­ber of agents and tokens.”

    algo­rithms agent-​​based multi-​​agent-​​systems network-​​theory nudge-​​targets

  • [1106.1821] Col­lec­tive Intel­li­gence, Data Rout­ing and Braess’ Paradox

    “We con­sider the prob­lem of design­ing the the util­ity func­tions of the utility-​​maximizing agents in a multi-​​agent sys­tem so that they work syn­er­gis­ti­cally to max­i­mize a global util­ity. The par­tic­u­lar prob­lem domain we explore is the con­trol of net­work rout­ing by plac­ing agents on all the routers in the net­work. Con­ven­tional approaches to this task have the agents all use the Ideal Short­est Path rout­ing Algo­rithm (ISPA). We demon­strate that in many cases, due to the side-​​effects of one agent’s actions on another agent’s per­for­mance, hav­ing agents use ISPA’s is sub­op­ti­mal as far as global aggre­gate cost is con­cerned, even when they are only used to route infin­i­tes­i­mally small amounts of traf­fic. The util­ity func­tions of the indi­vid­ual agents are not “aligned” with the global util­ity, intu­itively speak­ing. As a par­tic­u­lar exam­ple of this we present an instance of Braess’ para­dox in which adding new links to a net­work whose agents all use the ISPA results in a decrease in over­all through­put. We also demon­strate that load-​​balancing, in which the agents’ deci­sions are col­lec­tively made to opti­mize the global cost incurred by all traf­fic cur­rently being routed, is sub­op­ti­mal as far as global cost aver­aged across time is con­cerned. This is also due to ‘side-​​effects’, in this case of cur­rent rout­ing deci­sion on future traf­fic. The math­e­mat­ics of Col­lec­tive Intel­li­gence (COIN) is con­cerned pre­cisely with the issue of avoid­ing such dele­te­ri­ous side-​​effects in multi-​​agent sys­tems, both over time and space. We present key con­cepts from that math­e­mat­ics and use them to derive an algo­rithm whose ideal ver­sion should have bet­ter per­for­mance than that of hav­ing all agents use the ISPA, even in the infin­i­tes­i­mal limit. We present exper­i­ments ver­i­fy­ing this, and also show­ing that a machine-​​learning-​​based ver­sion of this COIN algo­rithm in which costs are only impre­cisely esti­mated via empir­i­cal means (a ver­sion poten­tially applic­a­ble in the real world) also out­per­forms the ISPA, despite hav­ing access to less infor­ma­tion than does the ISPA. In par­tic­u­lar, this COIN algo­rithm almost always avoids Braess’ paradox.”

    collective-​​intelligence search-​​algorithms figure-​​ground-​​error plan­ning nudge

  • [1108.0404] Exploit­ing Agent and Type Inde­pen­dence in Col­lab­o­ra­tive Graph­i­cal Bayesian Games

    “Effi­cient col­lab­o­ra­tive deci­sion mak­ing is an impor­tant chal­lenge for mul­ti­a­gent sys­tems. Find­ing opti­mal joint actions is espe­cially chal­leng­ing when each agent has only imper­fect infor­ma­tion about the state of its envi­ron­ment. Such prob­lems can be mod­eled as col­lab­o­ra­tive Bayesian games in which each agent receives pri­vate infor­ma­tion in the form of its type. How­ever, rep­re­sent­ing and solv­ing such games requires space and com­pu­ta­tion time expo­nen­tial in the num­ber of agents. This arti­cle intro­duces col­lab­o­ra­tive graph­i­cal Bayesian games (CGBGs), which facil­i­tate more effi­cient col­lab­o­ra­tive deci­sion mak­ing by decom­pos­ing the global pay­off func­tion as the sum of local pay­off func­tions that depend on only a few agents. We pro­pose a frame­work for the effi­cient solu­tion of CGBGs based on the insight that they posses two dif­fer­ent types of inde­pen­dence, which we call agent inde­pen­dence and type inde­pen­dence. In par­tic­u­lar, we present a fac­tor graph rep­re­sen­ta­tion that cap­tures both forms of inde­pen­dence and thus enables effi­cient solu­tions. In addi­tion, we show how this rep­re­sen­ta­tion can pro­vide lever­age in sequen­tial tasks by using it to con­struct a novel method for decen­tral­ized par­tially observ­able Markov deci­sion processes. Exper­i­men­tal results in both ran­dom and bench­mark tasks demon­strate the improved scal­a­bil­ity of our meth­ods com­pared to sev­eral exist­ing alternatives.”

    col­lab­o­ra­tion agent-​​based complex-​​systems emergent-​​design nudge-​​targets

  • [1102.2837] Effi­cient Pro­mo­tion Strate­gies in Hier­ar­chi­cal Organizations

    “The Peter prin­ci­ple has been recently inves­ti­gated by means of an agent-​​based sim­u­la­tion and its valid­ity has been numer­i­cally cor­rob­o­rated. It has been con­firmed that, within cer­tain con­di­tions, it can really influ­ence in a neg­a­tive way the effi­ciency of a pyra­mi­dal orga­ni­za­tion adopt­ing mer­i­to­cratic pro­mo­tions. It was also found that, in order to bypass these effects, alter­na­tive pro­mo­tion strate­gies should be adopted, as for exam­ple a ran­dom selec­tion choice. In this paper, within the same line of research, we study pro­mo­tion strate­gies in a more real­is­tic hier­ar­chi­cal and mod­u­lar orga­ni­za­tion and we show the robust­ness of our pre­vi­ous results, extend­ing their valid­ity to a more gen­eral con­text. We dis­cuss also why the adop­tion of these strate­gies could be use­ful for real organizations.”

    organizational-​​behavior com­plex­ol­ogy complexological-​​amusements agent-​​based com­pe­tence

Items of some interest…

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  • [1106.4577] Inter­ac­tive Exe­cu­tion Mon­i­tor­ing of Agent Teams

    “There is an increas­ing need for auto­mated sup­port for humans mon­i­tor­ing the activ­ity of dis­trib­uted teams of coop­er­at­ing agents, both human and machine. We char­ac­ter­ize the domain-​​independent chal­lenges posed by this prob­lem, and describe how prop­er­ties of domains influ­ence the chal­lenges and their solu­tions. We will con­cen­trate on dynamic, data-​​rich domains where humans are ulti­mately respon­si­ble for team behav­ior. Thus, the auto­mated aid should inter­ac­tively sup­port effec­tive and timely deci­sion mak­ing by the human. We present a domain-​​independent cat­e­go­riza­tion of the types of alerts a plan-​​based mon­i­tor­ing sys­tem might issue to a user, where each type gen­er­ally requires dif­fer­ent mon­i­tor­ing tech­niques. We describe a mon­i­tor­ing frame­work for inte­grat­ing many domain-​​specific and task-​​specific mon­i­tor­ing tech­niques and then using the con­cept of value of an alert to avoid oper­a­tor over­load. We use this frame­work to describe an exe­cu­tion mon­i­tor­ing approach we have used to imple­ment Exe­cu­tion Assis­tants (EAs) in two dif­fer­ent dynamic, data-​​rich, real-​​world domains to assist a human in mon­i­tor­ing team behav­ior. One domain (Army small unit oper­a­tions) has hun­dreds of mobile, geo­graph­i­cally dis­trib­uted agents, a com­bi­na­tion of humans, robots, and vehi­cles. The other domain (teams of unmanned ground and air vehi­cles) has a hand­ful of coop­er­at­ing robots. Both domains involve unpre­dictable adver­saries in the vicin­ity. Our approach cus­tomizes mon­i­tor­ing behav­ior for each spe­cific task, plan, and sit­u­a­tion, as well as for user pref­er­ences. Our EAs alert the human con­troller when reported events threaten plan exe­cu­tion or phys­i­cally threaten team mem­bers. Alerts were gen­er­ated in a timely man­ner with­out inun­dat­ing the user with too many alerts (less than 10 per­cent of alerts are unwanted, as judged by domain experts).”

    emergent-​​design multi-​​agent-​​systems engineering-​​design con­trol coor­di­na­tion nudge-​​targets

  • [1107.1322] Text Clas­si­fi­ca­tion: A Sequen­tial Read­ing Approach

    “We pro­pose to model the text clas­si­fi­ca­tion process as a sequen­tial deci­sion process. In this process, an agent learns to clas­sify doc­u­ments into top­ics while read­ing the doc­u­ment sen­tences sequen­tially and learns to stop as soon as enough infor­ma­tion was read for decid­ing. The pro­posed algo­rithm is based on a mod­eli­sa­tion of Text Clas­si­fi­ca­tion as a Markov Deci­sion Process and learns by using Rein­force­ment Learn­ing. Exper­i­ments on four dif­fer­ent clas­si­cal mono-​​label cor­pora show that the pro­posed approach per­forms com­pa­ra­bly to clas­si­cal SVM approaches for large train­ing sets, and bet­ter for small train­ing sets. In addi­tion, the model auto­mat­i­cally adapts its read­ing process to the quan­tity of train­ing infor­ma­tion provided.”

    text-​​classification natural-​​language-​​processing machine-​​learning nudge-​​targets

  • [1011.0362] Opti­miza­tion of arti­fi­cial flock­ings by means of anisotropy measurements

    “An effec­tive pro­ce­dure to deter­mine the opti­mal para­me­ters appear­ing in arti­fi­cial flock­ings is pro­posed in terms of opti­miza­tion prob­lems. We numer­i­cally exam­ine genetic algo­rithms (GAs) to deter­mine the opti­mal set of para­me­ters such as the weights for three essen­tial inter­ac­tions in BOIDS by Reynolds (1987) under ‘zero-​​collision’ and ‘no-​​breaking-​​up’ con­straints. As a fit­ness func­tion (the energy func­tion) to be max­i­mized by the GA, we choose the so-​​called the $gamma$-value of anisotropy which can be observed empir­i­cally in typ­i­cal flocks of star­ling. We con­firm that the GA suc­cess­fully finds the solu­tion hav­ing a large $gamma$-value leading-​​up to a strong anisotropy. The numer­i­cal expe­ri­ence shows that the pro­ce­dure might enable us to make more real­is­tic and effi­cient arti­fi­cial flock­ing of star­ling even in our per­sonal com­put­ers. We also eval­u­ate two dis­tinct types of inter­ac­tions in agents, namely, met­ric and topo­log­i­cal def­i­n­i­tions of inter­ac­tions. We con­firmed that the topo­log­i­cal def­i­n­i­tion can explain the empir­i­cal evi­dence much bet­ter than the met­ric def­i­n­i­tion does.”

    artificial-​​life network-​​theory sim­u­la­tion boids opti­miza­tion nudge-​​targets

  • [1106.5316] Online Cake Cut­ting (pub­lished version)

    “We pro­pose an online form of the cake cut­ting prob­lem. This mod­els sit­u­a­tions where agents arrive and depart dur­ing the process of divid­ing a resource. We show that well known fair divi­sion pro­ce­dures like cut-​​and-​​choose and the Dubins-​​Spanier mov­ing knife pro­ce­dure can be adapted to apply to such online prob­lems. We pro­pose some fair­ness prop­er­ties that online cake cut­ting pro­ce­dures can pos­sess like online forms of pro­por­tion­al­ity and envy-​​freeness. We also con­sider the impact of col­lu­sion between agents. Finally, we study the­o­ret­i­cally and empir­i­cally the com­pet­i­tive ratio of these online cake cut­ting pro­ce­dures. Based on its resis­tance to col­lu­sion, and its good per­for­mance in prac­tice, our results favour the online ver­sion of the cut-​​and-​​choose pro­ce­dure over the online ver­sion of the mov­ing knife procedure.”

    game-​​theory economic-​​crisis decision-​​making fair­ness nudge-​​targets