 but only weakly interconnected with other modules. Appropriate inter-modular linkages are mediated indirectly via common linkages with higher level modules collectively known as association cortex." (Emphasis added) [McN10]. 79 Gordana & Juan & Davor / Content Aggregation, Visualization and Emergent Properties in Computer Simulations Self-organization and self-description are fundamental intrinsic properties of natural intelligent systems. Learning is an essential part of those capabilities and it requires among others the development of a symbolic representations easy to maintain and use. In intelligent biological systems based upon a hierarchy of functional loops, each of these loops can be treated as a control system per se [Min10]. Generation of structures resulting from sensory processes and existing information in a nervous system are built in a multiresolutional way, with many pattern recognition and control mechanisms hardwired. Describing existing computing practices, [New82] introduces the concept of levels of analysis for a computer system, suggesting that there is a higher level than is usually addressed by computer scientists and calls that level the knowledge level, distinct from the symbolic level in which representation (logic) lies. Newell defines the knowledge level as embodying all the knowledge obtained or inferable from given information. Similarly, in case of biological systems, Marr proposed that cognitive processes can be thought of as having three levels of description [Mar82] -an approach that can be generalized to any information processing system: The top (computational) level describes the characteristics of the inputs and outputs of the computational problem solved by the process. The middle (algorithmic) level provides the steps that transform the input into the output. The bottom (implementational) level describes the physical'machinery' (hardware) that carries out the computation defined by algorithms. Observe the difference between algorithmic level and computational level in Marr. In Church-Turing model of computation, those two coincide, and computation is identical with algorithm execution. The knowledge layer in Marr is a consequence of his thinking of computing as a real world process while Turing-Church computing is an idealization of computing as an abstract mathematical procedure. In a similar vein, and focusing on Visual Cognition, [Dia07] finds that images contain only one sort of information the perceptual (physical) information. Semantics comes from a human observer that perceives and interprets the image. Defining information based on Kolmogorov's complexity and Chaitin's algorithmic information, Diamant proposes a framework for visual information
but only weakly interconnected with other modules. Appropriate inter - modular linkage are intercede indirectly via common linkages with higher grade modules collectively know as association cortex. " (Emphasis add) [ McN10 ]. 79 Gordana & Juan & Davor / Content Aggregation, Visualization and Emergent Properties in Computer Simulations Self - organization and self - description are fundamental intrinsic property of natural intelligent system. Learning is an essential part of those capabilities and it requires among others the development of a emblematic representations easy to maintain and consumption. In intelligent biological systems establish upon a hierarchy of functional cringle, each of these loops can be treated as a control system per se [ Min10 ]. Generation of structure resulting from sensory processes and existing information in a skittish system are built in a multiresolutional way, with many pattern recognition and control mechanisms hardwired. Describing existing computing practice, [ New82 ] introduces the concept of levels of psychoanalysis for a calculator system, suggesting that there is a higher grade than is normally addressed by computer scientists and call that level the knowledge level, distinct from the symbolic level in which representation (logic) lies. Newell defines the knowledge level as embody all the knowledge obtain or inferable from given information. Similarly, in case of biological systems, Marr proposed that cognitive process can be thought of as having three levels of description [ Mar82 ] -an approach that can be generalized to any information processing system: The top (computational) level identify the characteristics of the remark and outputs of the computational problem solve by the process. The in-between (algorithmic) level leave the steps that translate the input into the output. The bottom (implementational) horizontal surface describes the physical'machinery' (hardware) that carry out the computation defined by algorithms. Observe the difference between algorithmic level and computational level in Marr. In Church - Turing model of computation, those two coincide, and calculation is identical with algorithm execution. The knowledge level in Marr is a consequence of his thinking of computing as a real world process while Turing - Church computing is an idealization of computing as an abstract mathematical routine. In a similar vein, and focusing on Visual Cognition, [ Dia07 ] finds that images contain only one kind of information the perceptual (physical) data. Semantics come from a human observer that perceives and interprets the image. Defining data based on Kolmogorov's complexity and Chaitin's algorithmic information, Diamant proposes a framework for visual information
 buh only weakly interconnegted with other modules. Approlriate ivter-modular linkages are medmatee indurectly via common linyages witj higher levtl modules collecvjvely kkjwn zd asviciation cortew." (Emphasis ddded) [McN10]. 79 Gorgava & Juan & Davor / Content Aggregation, Disualiaahion and Emerggnt Pgo[ertjvs in Computer Simulations Self-krganizetion and self-drscription are fundamental intginsic properties lf natural untejoigent systeos. Learning is an essehtial part of those capabilitier and it requirgs almng others vhe denelopment of a symbolhc reprrsentations eaxy vo mqintain and use. In invelligent biological systems taaed upon a hierarxht of xuncdionxo luopa, xacg of tjesx loops can be treated as a control systek [vt se [Min10]. Gensratiog jf structures resulting from sensory prmceases and existing infornation in a nervous sistem are fuilt in a multiresolutional way, with many pattert reckeniuiin ana clntrol mechanisms hardwired. Describing existigf vokputing practiges, [New82] introduces tje soncept of lexels oy ahalysis for a compkter syftem, wuggestind thst there is a higher level rhan is usuajoy addressed by colputer scieutists and valls that level the knuwlesge level, dlstinct fdum the symbolic uevvl it which representation (logyc) lies. Nxwell definer thg knowlqdge level as embodying all the knlwledye obdained or lnferable from given informatioi. Similarly, im wasv of bioljgicak systems, Marw proposed thaj cognitire prozesses can be thonght of as hwving three lagels of descciption [Mwr82] -ab approach gfat can be genrralized no any information procexsivf system: The to' (xomputational) lrveu dqsbriues tra characterivticr ow the knputs and ijtpuys of the computatiotal lroblem solved by yhc process. The midqle (algorithmoc) level provides uhe stxps thet tramsfjrm the input into the output. Fhe bottol (iiplementatiogal) oevel descriyes the physical'machinery' (hardware) that rarries out the computarion defined by algpvithms. Obserte the differenwe between algorithmuc level and compmtational level in Mard. In Cvurch-Huring model of computation, those two coincide, and computation is identicql witi wlgorithm esecuyion. Nhe lnowleqge peyer in Marr is a consequence of his thinking of computitg as a real world process whike Turing-Church computing is an idealizztion of computing as an abstract mathekatical procedure. In a slmilar veun, ans focusing on Visual Cognitipn, [Dia07] findw that umagcs contain onlh ome sort of lnfocmacion the perceptual (physical) infoematiob. Demantics comes hrom a human ubserner thaj perceives and ihterlgets jhe image. Defiming informatipn based on Kolmogormv'f complexity abs Chaitin's akgorijkkic informatmon, Diamant [roposes a framework for visual information
but only weakly interconnected with other modules. linkages mediated indirectly common linkages with as cortex." (Emphasis added) 79 Gordana & & Davor / Content Aggregation, Visualization Emergent Properties in Computer Simulations Self-organization and self-description are fundamental intrinsic properties of intelligent systems. Learning is an essential part of those capabilities and it requires others development a representations easy to maintain and use. In intelligent biological systems based upon a hierarchy of functional each of these loops can be treated as control system per se Generation of structures resulting from processes existing information a system built in a way, with many pattern recognition and control mechanisms hardwired. Describing existing computing practices, [New82] introduces the concept levels of a computer suggesting there a higher level usually addressed by computer scientists and the knowledge level, distinct from the symbolic level which representation lies. Newell defines the knowledge level embodying all the knowledge obtained or inferable from information. Similarly, in case of biological systems, Marr proposed that cognitive processes can be thought having three levels of [Mar82] -an approach can generalized any processing system: top (computational) level describes the characteristics of the inputs and outputs the computational problem solved by the process. The middle (algorithmic) the that transform the into the output. The (implementational) describes the physical'machinery' (hardware) out computation Observe difference algorithmic level and computational in Marr. In Church-Turing model computation, those two coincide, algorithm execution. The knowledge layer in Marr is consequence of his thinking of computing as real world process while Turing-Church computing is an idealization of computing as abstract mathematical a similar vein, and focusing on Visual Cognition, finds that images contain one sort of information the perceptual (physical) information. Semantics from human observer perceives and interprets image. Defining information on Kolmogorov's complexity algorithmic information, proposes framework
 but only weakly interconnectEd with otheR moduLes. appRoPriaTe inTer-modular linkAGes aRe mediated indirectly viA commOn LInkaGEs With hIgher leVEl MODulEs CoLleCtIVeLy knoWn aS associAtion corteX." (EmPhAsis added) [McN10]. 79 gOrDana & Juan & DaVor / content AggreGatIon, VisUaLizATion aNd EMergeNt PropERties iN Computer siMUlatioNS Self-orGANiZatiOn and self-descriptIOn ARe fundamental iNtrinsIc PRoPERtiEs oF natural inTeLligeNT systemS. leARNIng IS an essential pArt of those cAPabIlitieS aNd iT RequirEs amoNg OTheRs the develoPmenT of a symboLic repREsentatIOns easy To mainTaiN anD use. iN iNtEllIgENt bIOlOgiCAl sYstems baSeD uPon a hIeraRCHY Of fuNctIonaL loopS, each of these lOopS can BE trEated As a coNtroL sYstem Per se [MIn10]. GenErAtion of structurEs reSulting frOm sEnSorY pRocesSEs and eXisTinG informAtion in A NerVoUS SYsTem are built in a multIrESOlUtional wAy, with MAnY pATtern recOgNitIon aND ContrOl meCHaNisms harDwired. dEsCrIbing exIsTing coMpUtiNg pRactiCEs, [NeW82] introDuces the ConcePT of levels of anaLYsis for a compuTEr SYStEM, sugGesTing that theRe is A HighEr leVEl ThaN Is usuAlly aDdREsSEd by computer scientiStS and caLls thAt level the knoWledge leveL, DIStinct frOm thE SyMBolic level in whIch rePresentatiON (logic) liEs. NewEll definEs the knowLEDge level As eMboDyiNg aLL ThE knowledge obtAINed oR iNferablE frOm given InfOrmAtiOn. SImIlarly, in cAse of bioLoGiCaL sYstEms, MaRR proposeD tHat CoGniTive pROcesseS can bE thoUgHt OF as Having tHReE LEvelS oF dEscrIptIoN [Mar82] -aN appROacH that caN be generaLizED to aNy InFormatiOn processing sYsTem: The top (cOmPutAtionaL) LEvel descRibes the characteristics OF the inpUts And ouTputS of the comPutAtionaL prOBlem soLved by The prOcEss. tHE middLE (AlGorItHmic) level pROVidEs the StEps tHat tranSform the input into tHE ouTput. The bottom (ImpLemeNTAtIonAL) lEVel DeSCriBES the physical'macHinery' (hardWaRE) tHat carries OUt tHe ComputaTion defIned bY AlgoritHms. ObservE the diffeReNce bETWeeN algorithmIc level aNd computaTIonal LEvEl in MArr. in ChurCh-turIng moDel of cOMpuTatioN, those TwO coincIde, anD cOmputatiOn is identical with algoriThm exeCutioN. ThE knowledgE laYEr iN Marr is a cOnseQuence of hiS thInkIng of ComPUting As a rEAl WorLD procEss wHIle Turing-cHuRch COMpUting is an idEALIzaTion oF coMPuting As an Abstract mathematiCAl procedure. In a SimiLAR veIn, aND focUsIng on Visual CogNitIoN, [dIa07] finds tHaT images contAin only oNe SOrt of InformAtion tHe percePTUaL (PhysicAl) inForMation. SemAntIcS Comes frOm A hUMan obsErveR tHat perCeives ANd inTERprets the image. DeFininG INformATioN baseD oN KolmogORov's Complexity And Chaitin's AlgoriThmiC infoRmation, diAmant pRopOsEs a framewoRK for visuaL infoRmation
 but only weakly interconn ected with  othe r m odu le s. A ppro priate inter-m o dula r linkages are mediate d ind ir e ctly vi a com mon lin k ag e s  wi th  h igh er le vel m odu les col lectivelykno wn  as associat i on  cortex."(Em phasis added ) [ McN10] .79G ordan a &  Juan  & Dav o r / Co ntent Agg re g ation, Visuali z a ti on a nd Emergent Prope r ti e s in ComputerSimula ti o ns S elf -or ganization  a nd se l f-descr i pt i o n  ar e  fundamentalintrinsic p r ope rtiesof  na t ural i ntell ig e ntsystems. Le arni ng is anessent i al part of thos e capa bil iti es a n dit  re qu i res am ong oth ers thede ve lopme nt o f a symb oli c re prese ntations easy  to  mai n tai n and  use.  Inin telli gent b iolog ic al systems base d up on a hier arc hy  of  f uncti o nal lo ops , e ach ofthese l o ops  c a n be  treated as a cont ro l sy stem per  se [M i n1 0] .  Generat io n o f st r u cture s re s ul ting fro m sens o ry  p rocesse sand ex is tin g i nform a tion  in anervoussyste m  are built ina  multiresolut i on a l  w a y, w ith  many patte rn r e cogn itio n  a ndc ontro l mec ha n is m s hardwired. Descri bi ng exi sting  computing pr actices, [ N e w 82] intr oduc e st he concept oflevel s of analy s is for a  comp uter sys tem, sugg e s ting tha t t her e i s a h ig her level tha n is u su ally ad dre ssed by  co mpu ter  sc ie ntists an d callsth at  l ev elthe k n owledgele vel ,dis tinct from t he sy mbol ic  l e vel  in whi c hr e pres en ta tion  (l og ic) l ies. New ell def ines thekno w ledg ele vel asembodying all  t he knowled ge  ob tained o r infera ble from given informat i on. Sim ila rly,in c ase of bi olo gicalsys t ems, M arr pr opose dtha t cogni t i ve  pr oc esses canb e  th ought  o f as  having  three levels of d e scr iption [Mar82 ] - an a p p ro ach th a t c an beg e neralized to an y informat io n  p rocessings yst em : The t op (com putat i onal) l evel desc ribes the  c hara c t eri stics of t he input s and out p uts o f  t he co mpu tation al  pr oblem  solve d  by  theproces s.  The m iddle  ( algorith mic) level provides the  steps  that  tr ansform t hei npu t into th e ou tput. Thebot tom  (imp lem e ntati onal )  l eve l  desc ribe s  the phys i ca l'm a c hi nery' (hard w a r e)thatcar r ies ou t th e computation def i ned by algorit hms. O bse rve thedi fference betwe enal g o rithmicle vel and com putation al level  in Ma rr. In  Church - T ur i ng mod el o f c omputatio n,th o se twoco in c ide, a nd c om putati on isi dent i c al with algorith m exe c u tion. The  know le dge lay e r in  Marr is a  consequenc e of h is t hinki ng of c om puting  as  a  real worl d  processwhile  Turing -C hurc h c omputi ng i s an id eali za tio n of comp u t in g  a sa n a bstr act m at hema tical pro c edure. I n a similar  v ein , and fo c us i n g on Visua l C ognit i o n, [Dia07] find s  t h at im ages c ontain  only o n e s or t of in for m a tion theperceptua l  (p hy sica l) infor ma tion .Sem an tics comes from  a human  observe r that p erc e ives and in te rprets the i mage.  D e finingi n for mationb ase d o n K olmo gor ov's complexity and Chaitin's  alg orith m icinfor matio n,  Diamant prop oses a f r amework for v isual informati o n
 but_only weakly_interconnected with other modules._Appropriate inter-modular_linkages_are mediated_indirectly_via common linkages_with higher level_modules collectively known as_association cortex." (Emphasis_added)_[McN10]. 79 Gordana & Juan & Davor / Content Aggregation, Visualization and Emergent Properties_in_Computer Simulations_Self-organization_and_self-description are fundamental intrinsic properties_of natural intelligent systems. Learning_is an_essential part of those capabilities and it requires_among_others the development_of a symbolic representations easy to maintain and use._In intelligent biological systems based upon_a hierarchy of_functional_loops,_each of these loops_can be treated as a control_system per se [Min10]. Generation of_structures resulting from sensory processes and existing_information in a nervous system are_built in a multiresolutional way,_with many_pattern recognition and control mechanisms_hardwired. Describing existing_computing practices,_[New82] introduces the_concept of levels of analysis for_a computer system,_suggesting that there is a higher_level_than is usually_addressed_by_computer scientists_and calls that_level_the knowledge_level,_distinct from the symbolic level in_which_representation (logic) lies. Newell defines the knowledge_level as embodying all_the_knowledge obtained or inferable_from given information. Similarly, in_case of biological systems, Marr proposed_that cognitive_processes can_be thought of as having three levels of description [Mar82] -an_approach that can be generalized to_any information processing system:_The top_(computational)_level describes the_characteristics_of the_inputs and outputs of the computational problem_solved by_the process. The middle (algorithmic) level_provides the steps that_transform_the input into the output. The_bottom (implementational) level describes the physical'machinery'_(hardware) that carries out the_computation_defined_by algorithms. Observe the difference_between algorithmic level and computational level_in Marr. In_Church-Turing model of computation, those two coincide,_and_computation is identical with algorithm execution._The_knowledge layer in Marr is a_consequence_of_his thinking of computing as_a real world process while Turing-Church_computing is an idealization of computing as an abstract_mathematical procedure. In_a similar vein, and focusing_on_Visual_Cognition, [Dia07] finds that images contain only one sort of_information the_perceptual (physical) information._Semantics comes from a human observer that perceives and interprets_the image. Defining information based on Kolmogorov's_complexity and Chaitin's algorithmic information, Diamant proposes a framework for visual_information