 processing, which explicitly accounts for perceptual and cognitive image processing. Understanding simulations and their underlying mechanisms is informative for several reasons, among others in order to understand our own mechanisms of grasping the reality, as human cognition in many ways resembles process of simulation and emulation. From the cognitive point of view, in order to conceptualize enormous flow of input data that bombards us through our sensory apparatus, we have to focus on limited amount of data organized in structures. Partly, as a result of evolution, this clusterization and aggregation of data happens in our nervous system automatically on the hardware level without our being aware of it (sub-symbolic information processing). From the results of neuroscience and cognitive science we are learning about the implementation of those computational mechanisms in living beings, which appear in a hierarchy of levels. Simulation, Emulation, Aggregation Over the last years, there have been several attempts to philosophically define computer simulation [Dur10]. Next we will briefly address two of such attempts that we consider the most prominent of the latest literature. We have picked them in the first place because they set the agenda for the contemporary philosophical discussion on computer simulations. The first one is due to Hartmann: "Simulations are closely related to dynamic models. More concretely, a simulation results when the equations of the underlying dynamic model are solved. This model is designed to imitate the time-evolution of a real system. To put it another way, a simulation imitates one process by another process. In this definition, the term 'process' refers solely to some object or system whose state changes in time. If the simulation is run on a computer, it is called a computer simulation." [Har96] The mayor drawback in Hartmann's definition is that it is too broad since it does not differentiate simulations from other similar activities such as imitation or emulation. As a matter of fact, he bases his definition of simulation on the concept of imitation, which he does not define. However simulation should be differentiated from imitation, since in the former case we expect to have knowledge of the target system whereas in the latter we do not. Something similar happens for the case of emulation. The second definition of computer simulation is due to Humphreys. In this case, the author strengthens the definition of computer simulation by claiming that: "A computer simulation is any computer-implemented method for exploring the properties of mathematical models where analytical methods are unavailable." [Hum90] Although Humphreys' definition is more precise than Hartmann's,
processing, which explicitly accounts for perceptual and cognitive image processing. Understanding simulations and their underlie mechanism is informative for several reasons, among others in orderliness to understand our own mechanisms of grok the world, as human cognition in many ways resembles process of simulation and emulation. From the cognitive point of view, in club to conceptualize enormous flow of remark datum that bombards us through our sensory apparatus, we get to focus on limited sum of data organized in structures. partially, as a result of evolution, this clusterization and collection of data happen in our nervous system automatically on the hardware level without our being aware of it (sub - emblematic information processing). From the results of neuroscience and cognitive science we are learning about the implementation of those computational mechanisms in live beings, which appear in a hierarchy of levels. Simulation, Emulation, Aggregation Over the last years, there have been several attempts to philosophically define computer simulation [ Dur10 ]. Next we will concisely cover two of such attempts that we consider the most outstanding of the latest literature. We have picked them in the first plaza because they set the agenda for the contemporary philosophical discussion on computer model. The first one is due to Hartmann: " Simulations are closely related to dynamic model. More concretely, a simulation results when the equations of the underlying dynamic model are solve. This model is designed to imitate the time - evolution of a real arrangement. To put it another way, a simulation imitate one process by another process. In this definition, the term' process' refer solely to some aim or system whose state changes in time. If the simulation is carry on a computer, it is call a computer pretense. " [ Har96 ] The mayor drawback in Hartmann's definition is that it is too broad since it does not differentiate simulations from other alike activities such as caricature or emulation. As a matter of fact, he bases his definition of simulation on the concept of imitation, which he does not specify. However model should be differentiated from imitation, since in the early case we expect to give birth knowledge of the target system whereas in the latter we do not. Something similar happens for the case of emulation. The second definition of computer simulation is due to Humphreys. In this event, the writer strengthen the definition of computer simulation by claiming that: " A computer simulation is any computer - implement method for exploring the properties of numerical models where analytic methods are unavailable. " [ Hum90 ] Although Humphreys' definition is more precise than Hartmann's,
 prlcessing, which explicitln accounts for pgrxeptuan and dognitivd image processing. Understanving simuoations and their undeflying mebhanisms us iiformative for sxberal rccsons, wmony ithers in ordet to understdnd our own mewhxnnsms of grasping the reality, as humag cogniyiln in many wayf rexqmblss process of simulation and emulafion. Frmm the cognitove point of view, in order to fonceptualize enorlous flow od in[yt data that bombards lv through kur sensory apparatus, we have tu focbs on limitgb amlont of data irganpzed in strucblres. Pastly, as a result of eyolutmon, rhis clusterization aid aggregation of daja happens iu our nervous system quromathcalny ov thd hzrvwade levfl xithout our being awarw of it (sub-symbolic igdormation prodessind). Srom the results of neuroscience and cocnifive science we are leaening about the implelentation of those computational mechanisms in living beincs, whmcf akpcwf ij a hierarchy of levels. Simulation, Emulation, Wfgtenation Over the jast years, yhfrr have been sexeral cftsmpts to philosophlcally qefinw computew sikulation [Dur10]. Next we will beiefly addrefw two of such attelpts that wz consoder yhe most prominent of tke latsst literatkre. We habd picked them in thv fisst plact because they set the agenva fox the covtemkorary [hilosophifal dlvcussion on computfr silunations. Thf first one is due to Hartmann: "Simulations arg cnosvly relatzd to cynamic modelf. More concretgly, a simblatiov results shen thx equations jf the underlflng dynamic kodel arq sooved. This muael is designec to imitcue the timw-evolution of a reel sisfem. To put it auuuhwr way, a simulstiun ymptaves oga process by anoghef procdss. In ukis aefimition, the term 'procass' defers solely to spmc object ir systei whose state changes in time. Iv the sioulatoon is run on a computer, it is camled a colpuber simulatiog." [Hav96] Thg mayor dracback in Hartmann's definition is that it is too broad sincw it does not diffetenuiate simulatmons fwom other similar activities wuch as imitation or emulation. As a mafter ox fach, he bases his definition of simulation on the concept of imitation, which he doxs not define. Howrver viiblation shonlv be differentiatvd from imitation, since in the furmer cave we expect to have knowledge ow the target rystem whereas in the lafter we co not. Something similar happenx for the case of emulatlon. The swcond definpjioi of computer simulayion iv due to Humphrens. In this casd, tne author shrenjthzns the definition of computer sinulatiin by claiming thav: "A computer rimulztion ys any computer-ijplejfnted method for ecploring the ptoperties of mathemanicwl models whert analytical mejhods arv unavailable." [Hum90] Althouch Humphreys' definition is more precise than Hartmahn's,
processing, which explicitly accounts for perceptual and processing. simulations and underlying mechanisms is others order to understand own mechanisms of the reality, as human cognition in ways resembles process of simulation and emulation. From the cognitive point of view, order to conceptualize enormous flow of input data that bombards us through our apparatus, have focus limited amount of data organized in structures. Partly, as a result of evolution, this clusterization and of data happens in our nervous system automatically the hardware level without being aware of it (sub-symbolic processing). the results neuroscience cognitive we are learning the implementation of those computational mechanisms in living beings, which appear in a hierarchy of levels. Simulation, Aggregation Over years, there been attempts philosophically define computer Next we will briefly address two that we consider the most prominent of the literature. We picked them in the first place they set the agenda for the contemporary philosophical on computer simulations. The first one is due to Hartmann: "Simulations are closely related to More concretely, a simulation when the equations the dynamic are This model designed to imitate the time-evolution of a real system. To put another way, a simulation imitates one process by another process. definition, term 'process' refers to some object or whose changes in time. If is on is a simulation." [Har96] The mayor in Hartmann's definition is that is too broad since from other similar activities such as imitation or As a matter of fact, he bases definition of simulation on the concept of imitation, which he does not However simulation differentiated from imitation, since in the former case expect to have knowledge the target system whereas in the latter we do Something happens for case of emulation. second definition of simulation is due In this the strengthens computer simulation by claiming that: "A simulation any computer-implemented method for exploring properties models where analytical methods are unavailable." [Hum90] Although Humphreys' definition is more precise than Hartmann's,
 processing, which explicitly Accounts foR percEptUal AnD cogNitiVe image processINg. UnDerstanding simulations And thEiR UndeRLyIng meChanismS Is INForMaTiVe fOr SEvEral rEasOns, amonG others in oRdeR tO understand oUR oWn mechanisMs oF grasping the ReaLity, as HuMan COgnitIon In manY ways rESembleS process oF sIMulatiON and emuLATiOn. FrOm the cognitive poiNT oF View, in order to cOnceptUaLIzE ENorMouS flow of inpUt Data tHAt bombaRDs US THroUGh our sensory aPparatus, we hAVe tO focus On LimITed amoUnt of DaTA orGanized in stRuctUres. PartlY, as a reSUlt of evOLution, tHis cluSteRizAtioN AnD aGgrEgATioN Of DatA HapPens in ouR nErVous sYsteM AUTOmatIcaLly oN the hArdware level wIthOut oUR beIng awAre of It (suB-sYmbolIc infoRmatiOn Processing). From tHe reSults of neUroScIenCe And coGNitive SciEncE we are lEarning ABouT tHE IMpLementation of those CoMPUtAtional mEchaniSMs In LIving beiNgS, whIch aPPEar in A hieRArChy of levEls. SimULaTiOn, EmulaTiOn, AggrEgAtiOn OVer thE Last Years, tHere have Been sEVeral attempts tO PhilosophicalLY dEFInE CompUteR simulation [dur10]. NEXt we Will BRiEflY AddreSs two Of SUcH Attempts that we consiDeR the moSt proMinent of the laTest literaTURE. We have pIckeD ThEM in the first plaCe becAuse they seT The agendA for tHe contemPorary phiLOSophical DisCusSioN on COMpUter simulatioNS. the fIrSt one is Due To HartmAnn: "simUlaTioNs Are closelY related To DyNaMiC moDels. MORe concreTeLy, a SiMulAtion REsults When tHe eqUaTiONs oF the undERlYINg dyNaMiC modEl aRe SolveD. ThiS ModEl is desIgned to imItaTE the TiMe-EvolutiOn of a real systEm. to put it anoThEr wAy, a simULAtion imiTates one process by anotheR Process. in tHis deFiniTion, the teRm 'pRocess' RefERs soleLy to soMe objEcT or SYStem wHOSe StaTe Changes in tIME. If The siMuLatiOn is run On a computer, it is calLEd a Computer simulAtiOn." [HaR96] tHe MayOR dRAwbAcK In HARTmann's definitioN is that it iS tOO bRoad since iT DoeS nOt diffeRentiatE simuLAtions fRom other sImilar actIvItieS SUch As imitatioN or emulaTion. As a maTTer of FAcT, he baSes His defInItiOn of sImulatIOn oN the cOncept Of ImitatIon, whIcH he does nOt define. However simulatiOn shouLd be dIffErentiateD frOM imItation, siNce iN the former CasE we ExpecT to HAve knOwleDGe Of tHE targEt sySTem whereaS In The LATtEr we do not. SoMETHinG simiLar HAppens For tHe case of emulation. tHe second definiTion OF ComPutER simUlAtion is due to HuMphReYS. in this caSe, The author stRengthenS tHE defiNition Of compUter simULAtIOn by clAimiNg tHat: "A compuTer SiMUlation Is AnY ComputEr-imPlEmenteD methoD For eXPLoring the propertIes of MAThemaTIcaL modeLs Where anALytiCal methods Are unavailaBle." [Hum90] althOugh HUmphreyS' dEfinitIon Is More precisE Than HartmAnn's,
 processing, which explici tly accoun ts fo r p erc ep tual  and  cognitive ima g e pr ocessing. Understandin g sim ul a tion s  a nd th eir und e rl y i ngme ch ani sm s  i s inf orm ative f or several  re as ons, among o t he rs in orde r t o understand  ou r ownme cha n ismsofgrasp ing th e  reali ty, as hu ma n  cogni t ion inm a ny  way s resembles proce s so f simulation a nd emu la t io n .  Fr omthe cognit iv e poi n t of vi e w, i n  or d er to concept ualize enor m ous  flowof  in p ut dat a tha tb omb ards us thr ough  our sens ory ap p aratus, we have  to fo cus  on  lim i te damo un t  of da tao rga nized in  s tr uctur es.P a r t ly,asa re sultof evolution,  th is c l ust eriza tionandag grega tion o f dat ahappens in ournerv ous syste m a ut oma ti cally on the  ha rdw are lev el with o utou r b ei ng aware of it (su b- s y mb olic inf ormati o npr o cessing) .Fro m th e resul ts o f  n euroscie nce an d  c og nitivesc iencewe  ar e l earni n g ab out th e implem entat i on of those co m putational me c ha n i sm s  inliv ing beings,  whi c h ap pear in  ah ierar chy o fl ev e ls. Simulation, Emu la tion,Aggre gation Over t he last ye a r s , therehave be e n several atte mptsto philoso p hicallydefin e comput er simula t i on [Dur1 0].  Ne xtwew i ll  briefly addr e s s tw oof such  at temptstha t w e c ons id er the mo st promi ne nt  o fthe  late s t litera tu re.  W e h ave p i cked t hem i n th efi r stplace b e ca u s e th ey  s et t heag endafort hecontemp orary phi los o phic al  d iscussi on on compute rsimulation s.  Th e firs t one is d ue to Hartmann: "Simula t ions ar e c losel y re lated todyn amic m ode l s. Mor e conc retel y,  as i mulat i o nres ul ts when th e equ ation sof t he unde rlying dynamic mod e l a re solved. Th ismode l is  de s ig n edto imi t a te the time-evo lution ofar ea l system.T o p ut  it ano ther wa y, as imulati on imitat es one pr oc essb y  an other proc ess. Inthis defi n ition ,  t he te rm'proce ss ' r efers  solel y  to  some  objec tor sys tem w ho se state  changes in time. If th e simu latio n i s run ona c o mpu ter, it i s ca lled a com put ersimul ati o n." [ Har9 6 ]The mayor  dra w back in H a rt man n ' sdefinitioni s tha t itist oo bro ad s ince it does notd ifferentiate s imul a t ion s f r om o th er similar act ivi ti e s  such as  i mitation or  emulati on .  As a  matte r of f act, he b as e s hisdefi nit ion of si mul at i on on t he  c o nceptof i mi tation , whic h  hed o es not define. H oweve r simul a tio n sho ul d be di f fere ntiated fr om imitatio n, sin ce i n the  former  c ase we  ex pe ct to have knowledge  of t he targ et  sys tem  where as i n the l atte rwedo not. S o m et h in gs imi larhappe ns  for  the case of emula tio n . The s ec ond d efinit i on o f computer  si mulat i o n is due t o  Hum p hr e ys. I n this  case,  the au t hor  s trength ens t he defini tion of c o mpu te r si mulation  b y cl ai min gthat: "A comput er simul ation is a ny com put e r-im p lement ed  method forexplo ri n g the p r o per ties of mat hem ati calmod elsw here analytical methodsareunava i lab le."[Hum9 0]  Althoug h  Hum phreys'd efinition ismore precise th a n H a rtma nn' s ,
 processing,_which explicitly_accounts for perceptual and_cognitive image_processing._Understanding simulations_and_their underlying mechanisms_is informative for_several reasons, among others_in order to_understand_our own mechanisms of grasping the reality, as human cognition in many ways resembles_process_of simulation_and_emulation._From the cognitive point of_view, in order to conceptualize_enormous flow_of input data that bombards us through our_sensory_apparatus, we have_to focus on limited amount of data organized in_structures. Partly, as a result of_evolution, this clusterization_and_aggregation_of data happens in_our nervous system automatically on the_hardware level without our being aware_of it (sub-symbolic information processing). From the_results of neuroscience and cognitive science_we are learning about the_implementation of_those computational mechanisms in living_beings, which appear_in a_hierarchy of levels._Simulation, Emulation, Aggregation Over the last_years, there have_been several attempts to philosophically define_computer_simulation [Dur10]. Next_we_will_briefly address_two of such_attempts_that we_consider_the most prominent of the latest_literature._We have picked them in the first_place because they set_the_agenda for the contemporary_philosophical discussion on computer simulations._The first one is due to_Hartmann: "Simulations_are closely_related to dynamic models. More concretely, a simulation results when the_equations of the underlying dynamic model_are solved. This model_is designed_to_imitate the time-evolution_of_a real_system. To put it another way, a_simulation imitates_one process by another process. In_this definition, the term_'process'_refers solely to some object or_system whose state changes in time._If the simulation is run_on_a_computer, it is called a_computer simulation." [Har96] The mayor drawback_in Hartmann's definition_is that it is too broad since_it_does not differentiate simulations from other_similar_activities such as imitation or emulation._As_a_matter of fact, he bases_his definition of simulation on the_concept of imitation, which he does not define. However_simulation should be_differentiated from imitation, since in_the_former_case we expect to have knowledge of the target system_whereas in_the latter we_do not. Something similar happens for the case of emulation._The second definition of computer simulation is_due to Humphreys. In this case, the author strengthens the definition_of computer simulation by claiming that: "A computer_simulation is any computer-implemented method for exploring_the properties of mathematical_models_where analytical methods are unavailable." [Hum90] Although_Humphreys'_definition_is_more precise than_Hartmann's,