 it is still too general. It is not clear what he means by exploration of properties of mathematical models. Let us try to unfold this. A major deficiency in Humphreys' concept is that it restricts computer simulations to mathematical models, which is clearly not accurate enough for characterization. Computer simulations are based on algorithms, but an algorithm not necessarily has to be based on a mathematical model, for 80 Gordana & Juan & Davor / Content Aggregation, Visualization and Emergent Properties in Computer Simulations it could be based on logical models as well as specifications of a system lacking of any mathematical or logical structure. Several other definitions have been discussed in recent literature, but Hartmann and Humphreys have set the agenda for philosophical analysis of computer simulations. The dilemma of computer simulations centers on the question of their value as tools for exploration of the real world. Many philosophers see the deficiency of simulation related to the materiality of experiments, which is not present in simulations. This claim is now known as the'materiality problem' of computer simulations and has its standard conceptualization: "in genuine experiments, the same'material' causes are at work in the experimental and target systems, while in simulations there is merely formal correspondence between the simulating and target systems [... ] inferences about target systems are more justified when experimental and target systems are made of the'same stuff' than when they are made of different materials (as is the case in computer experiments)" [Par09]. Three solutions are in place: the lack of materiality of computer simulations make them defective as tools for production of relevant and reliable information (for example [Gua02]; [Mor05]; [Gie09]); the presence of materiality in experiments is ultimately, unimportant for purposes of investigations of real world phenomena (for instance [Mor09]; [Par09]; [Win09]), or some kind of middle point where the physicality of the computer, that is, the actual physical states in which the computer is switched when computing, serves as the basis for making the case of causality within the computer. There is a forth solution to this problem presented by Barberousse, Franceschelli and Imbert [Bar09] who claim that the representational and predictive power of computer simulations does not depend upon physical capacities, but upon a detailed analysis of their semantic levels. In the following, definitions will be given in order to clarify ideas of simulation, emulation and aggregation. Emulation vs. Simulation: "One system is said to emulate another when
it is still too general. It is not clear what he mean by exploration of place of mathematical models. Let us judge to unfold this. A major deficiency in Humphreys' concept is that it qualify calculator simulations to mathematical models, which is clearly not accurate enough for characterization. calculator simulations are based on algorithms, but an algorithm not necessarily experience to be based on a mathematical model, for 80 Gordana & Juan & Davor / Content Aggregation, Visualization and Emergent Properties in Computer Simulations it could be establish on logical models as well as stipulation of a system lacking of any mathematical or logical social organization. Several early definitions have been discussed in recent literature, but Hartmann and Humphreys have set the agenda for philosophic analysis of computer simulations. The dilemma of computer simulations centers on the question of their value as tools for exploration of the real world. Many philosophers see the deficiency of simulation related to the materiality of experiments, which is not present in simulations. This title is now known as the'materiality trouble' of calculator simulations and has its standard conceptualization: " in genuine experiments, the same'material' cause are at workplace in the experimental and target systems, while in model there is merely formal correspondence between the simulating and target systems [... ] inferences about aim systems are more justified when experimental and target systems are made of the'same material' than when they are made of unlike materials (as is the case in computer experiments) " [ Par09 ]. Three solutions are in place: the lack of materiality of calculator simulations make them defective as tools for production of relevant and reliable information (for example [ Gua02 ]; [ Mor05 ]; [ Gie09 ]); the presence of materiality in experiment is ultimately, unimportant for purposes of probe of real universe phenomena (for case [ Mor09 ]; [ Par09 ]; [ Win09 ]), or some kind of middle item where the physicality of the computer, that is, the actual forcible states in which the computer is switched when computing, serves as the basis for making the case of causality within the computer. There is a forth solution to this problem presented by Barberousse, Franceschelli and Imbert [ Bar09 ] who claim that the representational and predictive ability of computer simulations does not count upon physical capacities, but upon a detailed analysis of their semantic levels. In the following, definitions will be given in decree to clarify ideas of simulation, emulation and aggregation. Emulation vs. Simulation: " One system is said to emulate another when
 it is still too general. It is not clear wkqt he keans gy explofation of properties of mathxmatucal nodels. Let us try to uvfold thid. A majoe dehiciency in Humpideys' cokeept jd thct it restricts gomputer sikulations to mdtfelatical models, which is clearly not accuraye enough for chwracueryzatjon. Computer simulations are based on algmrithms, but am algorithm not necessarilj had to be based on a mathematicql mjeel, for 80 Goraana & Juan & Davor / Conjent Aggregation, Visualization avd Emzrgent Propgxried in Computec Simujations it could be tased om logical modeks es wwll as specifications of a system lackigg of any mcthematical or logicao wtrucjure. Vevefql uthtr vefjnitiojs iave been djscussed in recent literature, nue Hartmann and Humphwers have set the agenda for philosophican ahalysis of computer simylations. The dilemma lf computqr simulations centers on the question of their vdlue es toilf dog exploration of the real world. Many philosoprsrx xee the deficicncy of simulation rflsjed to the matgrialitv or experiments, whicj is noj preswnt in siiulayions. This claim is now knoqn as the'matvriaoity problem' of colputer simuuatipns amd has its standard coneeptuamization: "in genuine sbperiments, the sxme'kaderial' causes are at work yn the ex'erimzntal ana tatget syftems, whilf in simulations there id mergly fosmal corredpondence between the simulatinj and target xyvteks [... ] infzrencex about targee systems are kore juftifidd when exierimentan and targee systems are lade of the'seme stuff' thab whwn they xre made of digferent mcuerials (as is the case in cokpujed experiments)" [Pcx09]. Uheee solutions sre in ppare: thq lack of matariauith of cumputer simmlagionx make them defectiva as tools for productook of relecant and reliable infprmation (for examppe [Gue02]; [Mor05]; [Jie09]); thr ptesence of materiality in experjments is ulbimately, unim[ortqnt for purppses of investigations of real world phxnomena (for instance [Moe09]; [Par09]; [Win09]), or some knnc of middle poine where tve physicality of thw computer, that ix, the actual physical statev in ahich the computer is switched when computing, serves as the basis for makung thx sase of cauaaliyy winhiu tke comptter. Vhere is a forth xolution to this problem presenved by Bartexousse, Franceschelli and Imbett [Bar09] who claio that the representatiohal and lredictive power of computer sikulations does not depenc upon pyysiczl capacitmes, but upon a detaiked anclysis of theur scmantic levels. In tme followijg, dtfinntions will be given in order to xlarift ldeas of simulatmon, emulatiok xnd afgregajion. Emulation vs. Simhpatiov: "One system os said to emukate another when
it is still too general. It is what means by of properties of to this. A major in Humphreys' concept that it restricts computer simulations to models, which is clearly not accurate enough for characterization. Computer simulations are based algorithms, but an algorithm not necessarily has to be based on a mathematical for Gordana Juan Davor / Content Aggregation, Visualization and Emergent Properties in Computer Simulations it could be based on models as well as specifications of a system of any mathematical or structure. Several other definitions have discussed recent literature, Hartmann Humphreys set the agenda philosophical analysis of computer simulations. The dilemma of computer simulations centers on the question of their value tools for the real Many see deficiency of simulation the materiality of experiments, which is simulations. This claim is now known as the'materiality of computer and has its standard conceptualization: "in experiments, the same'material' causes are at work in experimental and target systems, while in simulations there is merely formal correspondence between the simulating systems [... ] inferences target systems are justified experimental target are made the'same stuff' than when they are made of different materials (as the case in computer experiments)" [Par09]. Three solutions are in lack materiality of computer make them defective as for of relevant and reliable example [Mor05]; of in is ultimately, unimportant for of investigations of real world (for instance [Mor09]; [Par09]; middle point where the physicality of the computer, is, the actual physical states in which computer is switched when computing, serves as the basis for making the of causality computer. There is a forth solution to this presented by Barberousse, Franceschelli Imbert [Bar09] who claim that the representational and predictive of simulations does depend upon physical but upon a analysis of their In the definitions be to clarify ideas of simulation, emulation aggregation. vs. Simulation: "One system is to when
 it is still too general. It is noT clear what He meaNs bY exPlOratIon oF properties of mAThemAtical models. Let us try to UnfolD tHIs. A mAJoR defiCiency iN huMPHreYs' CoNcePt IS tHat it ResTricts cOmputer simUlaTiOns to mathemaTIcAl models, whIch Is clearly not AccUrate eNoUgh FOr chaRacTerizAtion. COMputer SimulatioNs ARe baseD On algorITHmS, but An algorithm not necESsARily has to be basEd on a mAtHEmATIcaL moDel, for 80 GordAnA & Juan & dAvor / ConTEnT aGGreGAtion, VisualizAtion and EmeRGenT PropeRtIes IN CompuTer SiMuLAtiOns it could bE basEd on logicAl modeLS as well AS specifIcatioNs oF a sYsteM LaCkIng Of ANy mAThEmaTIcaL or logicAl StRuctuRe. SeVERAL othEr dEfinItionS have been discUssEd in REceNt litEratuRe, buT HArtmaNn and HUmphrEyS have set the agenDa foR philosopHicAl AnaLySis of COmputeR siMulAtions. THe dilemMA of CoMPUTeR simulations centerS oN THe Question Of theiR VaLuE As tools fOr ExpLoraTIOn of tHe reAL wOrld. Many PhilosOPhErS see the DeFicienCy Of sImuLatioN RelaTed to tHe materiAlity OF experiments, whICh is not presenT In SIMuLAtioNs. THis claim is nOw knOWn as The'mATeRiaLIty prOblem' Of COmPUter simulations and hAs Its staNdard ConceptualizaTion: "in genuINE ExperimeNts, tHE sAMe'material' causEs are At work in thE ExperimeNtal aNd target Systems, whILE in simulAtiOns TheRe iS MErEly formal corrESPondEnCe betweEn tHe simulAtiNg aNd tArgEt Systems [... ] inFerences AbOuT tArGet SysteMS are more JuStiFiEd wHen exPErimenTal anD tarGeT sYSteMs are maDE oF THe'saMe StUff' tHan WhEn theY are MAde Of diffeRent materIalS (As is ThE cAse in coMputer experimEnTs)" [Par09]. Three SoLutIons arE IN place: thE lack of materiality of comPUter simUlaTions Make Them defecTivE as tooLs fOR produCtion oF releVaNt aND ReliaBLE iNfoRmAtion (for exAMPle [gua02]; [MoR05]; [GIe09]); thE presenCe of materiality in eXPerIments is ultimAteLy, unIMPoRtaNT fOR puRpOSes OF Investigations oF real world PhENoMena (for insTAncE [MOr09]; [Par09]; [WiN09]), or some Kind oF Middle pOint where The physicAlIty oF THe cOmputer, thaT is, the acTual physiCAl staTEs In whiCh tHe compUtEr iS switChed whEN coMputiNg, servEs As the bAsis fOr Making thE case of causality within tHe compUter. THerE is a forth SolUTioN to this prObleM presented By BArbErousSe, FRAncesChelLI aNd IMBert [BAr09] whO Claim that THe RepRESeNtational anD PREdiCtive PowER of comPuteR simulations does nOT depend upon phySicaL CApaCitIEs, buT uPon a detailed anAlySiS OF their seMaNtic levels. IN the follOwINg, defInitioNs will Be given IN OrDEr to clArifY idEas of simuLatIoN, EmulatiOn AnD AggregAtioN. EMulatiOn vs. SiMUlatION: "One system is said To emuLATe anoTHer When
 it is still too general.It is notclear  wh athe  mea ns b y explorationo f pr operties of mathematic al mo de l s. L e tus tr y to un f ol d thi s.  A  ma jo r  d efici enc y in Hu mphreys' c onc ep t is that it re stricts co mpu ter simulati ons  to ma th ema t icalmod els,whichi s clea rly not a cc u rate e n ough fo r ch arac terization. Compu t er simulations ar e base do na l gor ith ms, but an  a lgori t hm notn ec e s s ari l y has to be b ased on a m a the matica lmod e l, for  80 G or d ana  & Juan & D avor  / Conten t Aggr e gation, Visuali zation  an d E merg e nt  P rop er t ies in  Co m put er Simul at io ns it  cou l d b e ba sed  onlogic al models aswel l as spe cific ation s of  a  syst em lac kingof  any mathematic al o r logical  st ru ctu re . Sev e ral ot her  de finitio ns have bee nd i s cu ssed in recent lit er a t ur e, but H artman n  a nd Humphrey shav e se t the a gend a  f or philo sophic a lan alysisof  compu te r s imu latio n s. T he dil emma ofcompu t er simulations centers on th e  q u e st i on o f t heir valueas t o olsfore xp lor a tionof th er ea l  world. Many philos op hers s ee th e deficiencyof simulat i o n  related  tot he materiality of  expe riments, w h ich is n ot pr esent in  simulati o n s. Thiscla imisnow k no wn as the'mat e r iali ty  proble m'of comp ute r s imu lat io ns and ha s its st an da rd  c onc eptua l ization:  " inge nui ne ex p erimen ts, t he s am e' m ate rial' c a us e s  are  a twork  in  t he ex peri m ent al andtarget sy ste m s, w hi le  in sim ulations ther eis merelyfo rma l corr e s pondence  between the simulating and tar get  syst ems[... ] in fer encesabo u t targ et sys temsar e m o r e jus t i fi edwh en experim e n tal  andta rget  system s are made of the' s ame  stuff' thanwhe n th e y  a rem ad e  of  d i ffe r e nt materials (a s is the c as e  i n computer exp er iments) " [Par0 9]. T h ree sol utions ar e in plac e:  the l ack  of materi ality of  computer simul a ti ons m ake  themde fec tiveas too l s f or pr oducti on  of re levan tand reli able information (for e xample  [Gua 02] ; [Mor05] ; [ G ie0 9]); thepres ence of ma ter ial ity i n e x perim ents is  ul t imate ly,u nimportan t  f orp u rp oses of inv e s t iga tions  of real w orld  phenomena (for i n stance [Mor09] ; [P a r 09] ; [ W in09 ]) , or some kind  of  m i d dle poin twhere the p hysicali ty of th e comp uter,that is , th e  actua l ph ysi cal state s i nw hich th eco m puteris s wi tchedwhen c o mput i n g, serves as the  basi s for m a kin g the  c ase ofc ausa lity withi n the compu ter. T here  is a  forthso lution  to  t his proble m  presente d byBarbero us se,Fra ncesch elli a nd Im bert  [ Bar 09] who c l a im th at the  rep resen ta tion al and pr e dictivepow e r of co mp ute r simula t io n s  does notdep end u p o n physical capa c it i es, b ut upo n a de taileda nal ys is of t hei r semanticlevels. I n  th efoll owing, d ef init io nswi ll be given inorder to  clarify i deas o f s i mula t ion, e mu lation and a ggreg at i on. Emu l a tio n vs. S i mul ati on:  "On e s yste m  is said to emulate anot herwhen
 it_is still_too general. It is_not clear_what_he means_by_exploration of properties_of mathematical models._Let us try to_unfold this. A_major_deficiency in Humphreys' concept is that it restricts computer simulations to mathematical models, which_is_clearly not_accurate_enough_for characterization. Computer simulations are_based on algorithms, but an_algorithm not_necessarily has to be based on a mathematical_model,_for 80 Gordana_& Juan & Davor / Content Aggregation, Visualization and_Emergent Properties in Computer Simulations it_could be based_on_logical_models as well as_specifications of a system lacking of_any mathematical or logical structure. Several_other definitions have been discussed in recent_literature, but Hartmann and Humphreys have_set the agenda for philosophical_analysis of_computer simulations. The dilemma of_computer simulations centers_on the_question of their_value as tools for exploration of_the real world._Many philosophers see the deficiency of_simulation_related to the_materiality_of_experiments, which_is not present_in_simulations. This_claim_is now known as the'materiality problem'_of_computer simulations and has its standard conceptualization:_"in genuine experiments, the_same'material'_causes are at work_in the experimental and target_systems, while in simulations there is_merely formal_correspondence between_the simulating and target systems [... ] inferences about target systems_are more justified when experimental and_target systems are made_of the'same_stuff'_than when they_are_made of_different materials (as is the case in_computer experiments)"_[Par09]. Three solutions are in place:_the lack of materiality_of_computer simulations make them defective as_tools for production of relevant and_reliable information (for example [Gua02];_[Mor05];_[Gie09]);_the presence of materiality in_experiments is ultimately, unimportant for purposes_of investigations of_real world phenomena (for instance [Mor09]; [Par09];_[Win09]),_or some kind of middle point_where_the physicality of the computer, that_is,_the_actual physical states in which_the computer is switched when computing,_serves as the basis for making the case of_causality within the_computer. There is a forth_solution_to_this problem presented by Barberousse, Franceschelli and Imbert [Bar09] who_claim that_the representational and_predictive power of computer simulations does not depend upon physical_capacities, but upon a detailed analysis of_their semantic levels. In the following, definitions will be given in_order to clarify ideas of simulation, emulation and_aggregation. Emulation vs. Simulation: "One system is_said to emulate another_when