The notion of simulation - philosophical aspects

Anna Latawiec

The notion of simulation

-philosophical aspects

Studia Philosophiae Christianae 32/2, 165-176

1996

Studia Philosophiae Christianae A TK

32 (1996) 2

ANNA LATA W IEC

TH E Ν Ο Τ ΙΟ Ν O F SIM U L A T IO N - P H IL O SO P H IC A L ASPECTS*

1. The N otion and Types o f Simulation. 2. The Essence o f Simulation. 3. The Methodological Aspects o f Simulation.

The notion o f sim ulation appeared in scientific literature 30 years ago. However, in publications presenting practical examples o f sim ulation the explanation o f the notion itself is often om itted. Supposedly, such a situation results from an intuitive perception o f the notion and the authors’ concentration on the process and its final results.

1. T H E N O T IO N AND T Y PE S O F SIM U LA TIO N

The term sim ulation com es from the L atin w ord sim ulatio w hich means the re p resen ta tio n o r im itatio n o f the b eh a v io u r o f an object, group o f objects o r th e course o f a process th ro u g h the use o f an o th e r object, g ro u p o f objects o r process.

1.1. O BJECTIV E A PPR O A C H TO SIM U LA TIO N

The. objective a p p ro a c h to sim ulation is an a p p ro a c h th a t is based on identification o f a sim ulatio n w ith the m aterial o r form al object.

The objective a p p ro a c h to sim u latio n includes the follow ing interpretations:1

1) model (o p e ratio n al m odel: C.S. G re en b lat 1990; special m odel: D. C rookall, R. O x fo rd 1986; C.S. G re en b lat 1990)

2) actualisation o f the sim u lato r (D . C roo kall, R. O xford 1986) 3) tool (G .M . W einberg 1979, R .F . B arto n 1974, A .A .B . P ritsker,

C.D. Pegden 1976, T. R yś 1981, A. Pelech 1984)

4) technique (num erical: Т .Н . N a y lo r 1966; experim ental: W. Swita- lski 1987; p ro blem solving: G . G o rd o n 1969, 1975, T. R yś 1981) ‘ Tekst referatu wygłoszonego na 10tKInternational Congress o f Logic, M et­ hodology and Philosophy o f Science, August 19-25, 1995 - Florence, Italy.

1 Petny wykaz publikacji zawierających om aw iane określenia pojęcia symulacji znajdują się w pracy: A. Latawiec, Pojęcie symulacji i je j użyteczność naukowa. Warszawa 1993.

5) re p resen tatio n (J.M . P ro th , H .P. H illion 1990, A .A .B . P ritsker, C .D . Pegden 1976)

6) co m p u ter p ro g ram (H. Stanislaw 1986, J.M . P ro th , H .P. H illion 1990)

7) o p eratio n (G . B onham , E. C arter, J.W . H a rb a u g h 1969) 8) m eth o d o f confirm ing th a t the rules o f fun ctioning o f the

m aterial object are know n (G .M . W einberg 1979) 9) n a tu ra l b eh av io u r (A. Pelech 1984)

10) social p h en o m en o n (A. Pelech 1984)

O f special interest is the often observed id entificatio n betw een the n o tio n o f sim ulation an d th e m eth o d o f co nfirm ing th a t the rules o f fun ctio ning o f the m aterial object have been u n d ersto o d . It is obvious th a t the correct co n stru c tio n o f a system representing the original one requires p ro fo u n d know ledge a b o u t the original. I f we know the in p u t an d the re su ltan t o u tp u t states, then it is possible to learn a b o u t the in terio r o f the sim ulated object. In o th er w ords, by changing the in p u t p aram eters it is possible to o b ta in the o u tp u t states th a t agree w ith the real b eh a v io u r o f the system. T his is a m eth o d o f learning a b o u t th e system ’s interio r. As G .M . W einberg p u ts it, we ’’discover” the system ’s in terior. T herefore, if we succeed in co n stru c tio n o f a system th a t response to the given in p u t p aram eters is in accordance w ith o u r expectations, we m ay say th a t the essence o f the o b ject’s b eh a v io u r has been discovered, an d the sim ulatio n w as fruitful.

L et us p u t to g eth er an d consider the p ro p o sals identifying the n o tio n o f sim ulation w ith som e o f its in terp re tatio n s, i.e. the num erical, experim ental an d p ro b lem solving techniques o r the m eth o d o f confirm ing th a t the functioning o f the m aterial object is u n d ersto o d . A s a result we have a num erical m eth o d , a m eth o d or technique o f co nd ucting experim ents, a m eth o d o f solving problem s o r a m eth o d o f confirm ing th a t th e rules o f functio nin g o f the system u n d e r exam in atio n have been u n d ersto o d .

T o sum up, we m ay say th a t the objective a p p ro a c h to sim ulation inevitably leads to its identification either w ith a m aterial object (tool, physical m odel) o r a ’’fo rm a l” object (m athem atical m odel, m eth od , ap p ro ach , rep resen tatio n , sociological pheno m en o n , op eratio n).

1.2 O PER A TIO N A L A PPR O A C H TO SIM U LA TIO N

H ereinafter, by the term operational approach to simulation, a certain activity o r proceeding will be assum ed. S im ulation research a n d analysis m ade by their au th o rs, enable un derlining o f the follow ing activities :

1. modelling (by w ide range o f m eans), nam ely : m akin g use o f the model itself, c o m p u te r-a id e d m odelling an d c o m p u te r-a id e d research an d analysis

2. program m ing (widely u n d ersto o d ), nam ely : a co m p u ter p ro g ram execution, m ak in g use o f co m p u ters’ h ard w are and softw are tools and resources, c o m p u te r-a id e d m odelling

3. representing (or transfo rm ing): im itatio n, em ulation , tracking, m onitoring, d uplicating

4. reality’s fragm ent research an d analysis : beh av io u r analysis, individual cases analysis

5. activity 6. experimenting

Similarly w ith th e object a p p ro a c h an d the o p eratio n al ap p ro ach , more in fo rm atio n m ight be included indirectly o r in a hidden form .

Therefore, the o p eratio n al ap p ro ach o f sim ulatio n, results in its equivalence w ith one o f the follow ing activities :

1. Creating an d m ak in g use o f the m odel

2. Research, analysing an d experim enting (also c o m p u ter-aid ed ) 1.3 SYM BOLIC A PPR O A C H TO SIM U LA TIO N

Hereinafter, by the term sym bolic approach to sim ulation, its form al description based u p o n the n o ta tio n o f rules set w ithin a certain domain, will be assum ed.

Many au th o rs recognise the fact th a t form alising o f n o ta tio n , its consideration, etc. - proves the u n d ersta n d in g o f m entio ned dom ain. Actually, an extensive know ledge o n th e essence an d fu nction in g o f the notion is necessary fo r its form alising. In case o f the n o tio n o f simulation, a try to define a sim u lation process itself has tak en place. It is not, how ever, the one sym bolically seen an d expected by us.

The p ro p o sals o f M . Bunge, F. Pichler an d M . L ubań ski illustrate the third type o f the sim ulation ap p ro ach .

The first ap p ro ach stresses analo gies’ relatio n, a so rt o f sim ilarity between the objects. It is assum ed th a t the original an d its m odel should be ” in fec tio n -lik e” analogous. H aving said th a t, we state th a t a high level o f sim ilarity an d ad e qu acy betw een them sh ou ld take place, b u t m ention ed adeq uacy should n o t be m ean t as an identity. We talk on sim ulation in term s o f creating the real m odel, fo r example a sm all m odel o f a ship, so still the ad equacy is provided when fu nction graphics are presented. Bunge assum es th a t the simulation is an unsym m etrical, reciprocal an d tran sitio n al relation.

A m athem atical d escription m akes a p o in t o f the original object and its b eh a v io u r em ulatio n, an d in a form al w ay expresses an idea - that the sim ulation is a co n stru c tio n o f the m o d el’s statu s history

- as it w ould have been the o riginal’s one. T h a t is an exam ple o f the em u latio n by a sim ulating process. It does n o t address special situ atio n s concerning, fo r instance, a fa cto r o f tim e gone. N ev ert­ heless, we can easily see th a t b o th versions o f sym bolic sim ulation descriptions are ju s t a form al set o f expressions, ap pearin g in two previously m entioned type proposals.

2. T H E ESSEN CE O F SIM U LA TIO N

D escriptions presented above give us a p ictu re o f views an d their changes, w hich are depen d en t on o th er science an d technologies’ progress. A s fa r as new technologies becom e available, p articularly the m icroco m puters, the sim ulation m eth o d itself, alth o u g h h etero ­ geneously seen, com es in to w ider areas o f technology an d science. It becom es a m eth o d o r a tool, w hich is m ore an d m ore willingly and efficiently used - since its superiority over o th er scientific research m eth o d s an d tools has been recognised. T he sim ulation process in co n ju n ctio n w ith the tim e an d p u rp o se aspects is underlined in m any views an d analysis.

O ne o f the im p o rtan t factors o f the sim ulation notion, seems to be its relation w ith the tim e aspect. It gives a possibility o f m o nitoring the results, tracking an d recording the changes in status o f the sim ulated system — w ithin certain time fram es. In consequence, it m ay be seen as a source o f d a ta to predict the results o f the real system itself.

A n o th e r aspect com ing from the sim ulatio n, concerns the in ­ violability o f the real system . Since the sim ulation process m akes use o f its m odel only, th e real system rem ains unchanged. T his very feature, plainly specific, is often u n d ersto o d as the p rim ary criterion in choosing the m eth o d o f sim ulating the reality. T here exist a n u m b er o f cases, w hen sim ulation is the only applicable m eth o d o f getting to know the reality. W hen researched object, for exam ple a h u m an b rain , a com p an y business ad m in istratio n , etc. - is to be m o n ito red in term s o f its reactions on certain stim ulation , then the only p ro p e r w ay to han d le th a t is the sim u lation , m ainly co m ­ p u te r-a id e d .

N ow , let us consider w hether n o tio n al role o f sim ulation has any im p o rta n t im p act o n its value, particularly w hen co m p u ter-aid ed . It seems th a t it is n o t th e case, since th e sym bolic m odels are com m only used in th e scientific research.

O ne can say th e c o m p u te r-a id e d sim ulation is n o t really a sim ula­ tion in term s o f its w o rd exact m eaning, o r even th a t it has n o th in g in com m on w ith th a t. Such an opinion is sh ared m ainly by the physical sim ulation su p p o rters, w ho take in to ac co u n t its intuitive aspect. In

the light o f m entioned pro p o sals, a purely n o tio n al c o m p u ter-aid ed processing o f the sym bolic m odel, expressed in a certain p ro g ra m ­ ming language, is a sim ulation, too. T he only difference is th a t the com puter-aided sim ulation is o f a n o th e r type, in the sense o f its intuitive u n derstandin g.

Having agreed th a t the sim ulation is a form o f representing, transform ing, em ulating o r im itating - it is allow ed to d o th a t in any possible way - as long as the relations betw een the original and its model rem ain com patible. T h a t is w hy, we shall agree th a t the symbolic re p resen tatio n is one o f m any possible ways.

There also exists quite oppo site o pinion saying the sim ulation addresses m ainly the relations betw een the m odels a n d the co m puter. It is believed th a t in such a case, a purely n o tio n al sim ulation is seen as an exactly m ean t m ethod. F u rth erm o re , we shall stress the fact th a t the sim ulation is an artificial represen tatio n o f the reality.

It has been suggested th a t a full u n d ersta n d in g o f the sim ulated object o r system beh av io u r is needed before yo u proceed w ith the simulation. C ertainly, a know ledge o f th e system is necessary to construct its sim ulation m odel, b u t in m any cases the sim ulation is performed in o rd e r to get m ore in fo rm atio n o n its original, like its behaviour, for instance. Som etim es, before getting started , o u r knowledge m ight be p artia l o r ju st very p o o r — anyw ay, there is a need to know researched object on a m inim al level, so you will be able to co n stru c t its ap p ro x im ate m odel first. M o re d a ta a b o u t the object can be found by com p arin g the sim ulation results, tak en from and based upon various values o f entered p aram eters. If the results are those o f expected before processing, it will show o u r good knowledge o f the original, an d then we m ay recall G . M . W einberg words : ’’the black box is ours an d we can read it” . It will also m ean we proved o u r u n d ersta n d in g o f the original object.

If, how ever, the results do n o t feet to o u r expectations, it will show a wrong co n stru c tio n o f the m odel. T hen, according to th e sim ulation method rules, we will have to m odify the m odel, so next tim e the results should be positive. O f course, co n stru ctin g and im p ro ving the model, we will extend o u r know ledge o f its original.

Searching for the essence o f sim ulation, we discover th a t all recalled expressions and descriptions, carrying the m ost im p o rtan t inform ation in a hidden o r direct way, divide its stress o n the objective, operational and symbolic app roach. All types o f approaching:

1. relations betw een the sim ulation an d the m odel (o f different types) 2. the statu s chan ges’ dynam ics

3. inviolability o f th e original 4. a precise d escription o f a p u rpo se

In b o th sym bolic ap proaches, an existence o f sim ilarity relation - o r ju st analo gy - has been underlined. A certain tool is needed to illustrate such a relation, and it can be the m odel, w hich is to cap tu re those sim ilarities an d analogies. Sym bolic ap pro ach es m entioned before, above present the fun d am en tal ideas o f sim ulation in a different way. F ro m now on, we will exclude th e sym bolic a p p ro ach as a different way o f presenting the n o tio n o f sim ulation in b o th objective an d o p eratio n al versions.

T he objective ap p ro ach o f sim ulation often shows its certain aspects in a hidden w ay and a t the sam e tim e — the sam e aspects are very clear in term s o f the o p eratio n al ap p ro ach —- an d vice versa. F o r exam ple, w hen the objective ap p ro ach clearly addresses the m odel, then the o p eratio n al ap p ro ach includes the sam e m odel ju st in term s o f representation. As we well know , the represen tatio n s take place by m aking use o f som e tools, m ainly by the prop erly p rep ared m odels.

T h a t is why, we shou ld ad m it th a t b o th ap p ro ach types reciprocal­ ly com plem ent each o th er in highlighting the m ost im p o rta n t aspects o f the n o tio n o f sim ulation. T o sum m arize, we agree th a t searching fo r the essence o f the sim ulation n o tio n , we should take into account all its elem ents, p u t in a clear or hidden form - an d expressed by bo th objective an d o p eratio n al approaches.

The dynam ics o f the sim ulation, stressed m any times already, shows decreasing o r increasing o f the tim e scale. It is one o f the m ost im p o rtan t conditions for perform ing the sim ulation process. There exist m any different processes, which are difficult or even im possible to research and analyse, due to the length o f their tim e scale. In o ther w ords, the real processes last for a very long period o f time, like for exam ple the evolution process dem anding a m acro tim e scale. There are examples o f a very sho rt time scale, as some genetic phenom ena - an d it is simply im possible to track them in the real-tim e scale - from purely technological reasons. Therefore, there exists a possibility to represent o r ju st sim ulate the real-tim e scale during the sim ulation process, and a suitable time scale variable is needed for that. Similar situations take place when sim ulating the original object o f a size th a t disables their direct analysis. It m eans we use the process o f sim ulation w hen the original object size (p ut in m ic ro - o r m acro-scale) m akes it im possible to m on ito r, experim ent or research the original object, for instance the evolving galaxy, gens, biology (poi. Biocenoza).

N ow , takin g into acco u n t o u r consid eratio n s o f this ch ap ter, we will try to form a conso lidated definition o f the sim ulation, by b o th its a p p ro a c h an d its essence.

T he sim ulation is a usage o f a m aterial o r form al object (objective ap p ro ach ) in o rd e r to co n stru c t an d op erate o r research an d

experiment its m odel (o p eratio n al ap p ro ach ), which gu arantees the inviolability o f the real system an d provides the statu s ch an ges’ dynamics, by representing decrease o r increase o f the tim e scale and the object size - an d by do in g so - leads to achieving precisely described purpose.

3. T H E M ET H O D O L O G IC A L A SPECTS O F SIM U LA TIO N

We can address the sim ulation in b o th ’’p erso n al” an d so­ cial-cultural term s. T he first one covers any events o f individual human life. T hose are the unconscious situ atio n s from the early childish form s o f b ehav iour, like ’’playing h o m e” , im itatin g the parents, playing roles in variou s gam es, etc. L ate r on, a person learns to have ’’new faces” , m anners, hab its, so she/he can better m eet o th er persons’ expectations. A ctually, she/he sim ulates a good em ployee, a politician, a p aren t — always w hen it does n o t (fully) take place in reality. Such a ’’p erso n al” aspect o f the sim ulation is analysed by psychologists, psychiatrists (w hen the sim ulatio n becom es a sickness

I illness) an d sociologists.

As fa r as the so cial-c u ltu ral sim ulation aspects are concerned, the simulation m eans in ten tio n a l form s o f behavio ur, b u t first o f all — a heuristic a n d an ticip atio n m eth o d . T h a t is w hy, it is used to m o n ito r the results o f tak en decisions an d to trac k the progress o f certain activities.

Some o f the m ethodological aspects will be show n in this p a rt o f article now.

3.1. SIM U L A T IO N AS A M E T H O D

For the m ajo rity o f au th o rs, the sim ulatio n is a m eth o d o f system research an d analysis. By the term m ethod, we m ainly u n d ersta n d a rule o r a w ay to reach researched reality, o r a w ay to analyse that. To put it differently, it is a repeated action, so rt o f algorithm based upon a certain set o f rules.

It should be stressed th at a certain constant algorithm is being formed - and the separate steps are executed according to it - a problem specification, a model description, creating a program , execution o f that program, its verification, its validation, results interpretation and the conclusions. Each o f m entioned steps m ay be m ore complex.

The sim ulatio n is then n o t only an objective system research method, b u t also the en try p o in t fo r fu rth e r m ethodological p ro c ed u ­ res.

3.2. SIM U LA TIO N AS T H E EN TR Y PO IN T FO R T H E D ESC R IPTIO N The sim ulation m odel is co n stru cted in such a w ay th a t it allows to m o n ito r researched system ’s changes, the activities’ progress an d researched o bject’s stru ctu re itself. O n the one h a n d - the algo rithm includes a know ledge o f the sim ulation m odel and the o b ject’s description, on the o th er h an d - the ru n n in g p ro g ram illustrates the activities’ progress an d the o b ject’s status. In this sense, we can even stress th a t sim ulation is a description. T he sim ulation m odels describe the reality in its closest way.

W hen we research the m odel o f a gigantic b u b b le -le a f (pol. pęcherzo-listek), then at the sam e tim e its d escription is available; w hen we proceed w ith the m odel o f how the w eather influences on a certain insect type, we are able to have a description o f any events ca p tu red by the experim enter - an d by changing the m odel p aram e­ ters, we get a full p icture o f any possible situ atio ns. In this w ay, we use the description to co n stru ct the m odel - an d in parallel, th an k s to the sim u latio n ’s results, we can share its description w ith o th er users.

W hen we recall the steps o f the sim ulation process, then we will pay a tten tio n to a need o f given research precise description. T here m ust be a p u rp o se in any scientific activity. O ne o f them , as m entioned before, can be a clarification o f the process o r event. A t the sam e time, it becom es clear th a t the necessary co n d itio n fo r such a clarification is ju s t a precise description, expressed in a suitable language. So the description is a so rt o f the stage o f scientific research, in w hich the results are recorded, an d m entioned stages co rresp o n d w ith the scientific problem s to solve.

The n atu re’s description takes place indirectly, namely in the light o f research m ethods and is expressed in m ore and m ore specialised language. So we m ay say that the sim ulation m ethod is a sort o f an explorer’s preparedness to describe the real world. T he sim ulation model behaviour’s m onitoring is the entry point for the description o f reality.

T he sim ulation m ight be trea ted as the en try p o in t for a n atu ra l o r artificial, real o r hypothetical reality ’s description - an d th an k s to th a t - it is a first stage in creating th eo ry concerning certain process o r reality. O n the o th er h an d , the sim ulation plays a role o f con firm atio n o f previously form ed theories.

3.3. E X PE R IE N C E AS A SIM U LA TIO N

T he science often recalls the experience, trea tin g it as a specific type o f connection betw een a h u m an being an d the reality.

A n experim ent is a cognitive pro cedure, assum ing a sensual in fo rm atio n as a w ay to solve a problem - b u t the in fo rm atio n itself is insufficient.

The experim ent is a kind o f a dialogue betw een us an d su rro u n d in g reality. D ialogue d o n e by the experim ent is a very special type o f procedure, when the reality is cro ss-exam ined by us. T he answ ers for all raised questions are carefully recorded. T h eir im p o rtan ce is evaluated according to the rules set u p d u rin g a design phase o f the experiment. T he reality often rejects given hypothesis, b u t still remains the m ain criterion o f the answ ers’ acceptance.

An experim enter tries to check the circum stances, u n d er w hich the process goes on - and w hen he succeeds - he takes a certain adv an tag e over the observer, w ho ju st loo ks at the ru n n in g process, having n o influence on th at. Since the experim enter m ay interfere w ith the process w henever he wishes to, he can p ro p erly prep are him self for observation. He is able to rep eat his research m any times an d then compare its results. He also can system atically change th e co nd itio ns and then analyse their im p act on the resu lts’ changes.

A theoretician raises certain question s to the experim enter, w ho is tries to find o u t the answ ers by his experim ents. T he theoretician shows the way o f research to the experim enter, alth o u g h the later is partly a theoretician him self, since he uses th eo ry from the beginning o f its design. T he experim enter m ay exclude certain question s due to his research, an d those questions are n o t im p o rta n t to him anym o re in terms o f the scientific experim ent. T his reciprocal relatio n betw een the theory and experim enting is p articu larly pow erful an d clear in practice. Each experim ent is based up o n certain th eo ry a n d is processed for its needs. W hen experim enter u nd ertak es the research, he has to p rep are it in accordance w ith certain know ledge and theory.

Com paring o u r know ledge o f the sim ulation w ith o u r know ledge o f the experim ent, we m ay find ou t th a t the sim ulation is a form o f the scientific experim ent, which is heuristic, does som e checking an d is practically useful. A ny problem faced by experim enter is also faced by the sim ulator. T he sim ulative experim ent has to be carefully designed an d processed in accord ance w ith certain know ledge (and certain theory). S im ulators them selves trea t the sim u lation as a type o f experiment. It is w o rth to no te th a t also in case o f the sim ulatio n, it happens th a t d u ring the experim ent, by chance, a discovery o f another p h en o m en o n o r certain co rrelatio n m ay tak e place.

Therefore, it m ay seem to som eone th a t there is no difference between sim ulation and experim ent. H ow ever, the deeper analysis shows a n u m b er o f significant differences. T h e m ost im p o rta n t one is a possibility o f repeating any n u m b er o f the sim ulative experim ents, all of them processed u n d er unchanged circum stances w ith the param eters required by the experim enter. In case o f experim ents held in laboratories, there is a possibility o f very m in o r co n d itio n s’

changes, w hich m ay re tu rn significant changes o f the results a n d their in terp re tatio n .

A possibility o f repeating is one o f the aspects o f the experim ent an d the sim ulation. A n o th er, equally im p o rta n t one, is the in­ violability o f researched object. T he scientific experim ent (both heuristic on e an d decisive one) is lim ited to the events, which neither ethical d o u b ts o f the experim enter n o r technical difficulties appeain. W e m ean by those all such situ atio n s w hen researched object m ay be chan ged o r even d am aged (for instance a h u m an b rain), or situations w hen the tim e scale or the size scale h as to be changed. T he sim ulative experim ent is then the only possible to proceed w ith. T he researched object has a significant influence o n choosing a type o f the experim ent. All the experim ents m ay be processed on a living or lifeless, n atu ra l o r artificial object - only w hen it will n o t interfere w ith the system th a t m ight change the essence o f researched object. It is obvious th a t in m any cases the research m ay, on p u rpo se, change system o bject’s essence.

O u r co nsiderations on the sim ulation an d the experim ent can be sum m arised as follow s : there is a clear analogy betw een the sim ulation an d p a rtic u la r types o f experim ents, nam ely scientific and practically useful ones. A s in case o f the scientific experim ent, the sim ulation is based u p o n the sam e heuristic an d verifying purposes. P ractically useful experim ents an d sim ulation are processed in ord er to find o u t optim al applicable solutions. H av ing agreed on certain differences betw een the experim ent a n d the sim ulation, we m ay how ever ad m it those tw o are reciprocally com plem entary m ethods.

3.4 S IM U L A T IO N AS T H E E N T R Y PO IN T FO R T H E TH EO R Y N ow , let us consider the relations betw een the sim ulation an d the theory.

T he first m eaning o f the term theory is u n d ersto o d as a hypothesis used to resolve a certain research p rob lem an d it suggests an existence o f a link betw een th e sim ulation an d the hypothesis, leading to find ou t the resolu tion. T he th eo ry is trea ted ju s t as a verified hypothesis, a n d it is crucial to get an answ er for ’’w h a t - i f ’ questions, th an k s to a n d based on th e sim ulation. R asing such a q uestion, we base on the previously expressed hypothesis concerning the considered problem . T he entire sim ulative experim ent, a t its initial stage, is processed according to certain hypotheses th a t are taken due to the rules o f searching fo r a co n firm a tio n o r rejecting o f a proposed answ er.

In case o f the term theory, m ean t as m ethodologically and n o tio n ally co h eren t system o f theorem s, the sim ulation related w ith it

does not seem to fulfil the criteria set. T h a t is because the sim ulation is not a system o f theorem s. T he sim ulation is, how ever, related w ith a suitable n o tio n al a p p a ra tu s, like : a m odel, a scheme, a pro g ram , a verification, etc.

These n otio ns com e from o th er do m ains, m ainly from the com puter science an d cybernetics, b u t also from o th er areas linked with p artic u la r sim ulation m odels, so for exam ple - w ith the economics, biology, m edicine, etc. - o r w ith p artic u la r theories, like the Theory o f Decisions, o f G ra p h s an d o f G am es - w hich are used as the auxiliary tools. N o rules are set in the definition o f a theory, so the simulation can n o t be seen as a th eo ry in term s o f the second approach.

A com parison o f the th eo ry an d th e practice, show s the first one as a systematised know ledge clarifying a given d o m ain o f reality, which is much m ore convenient due to the scientific theories. T he th eo ry is a logical scheme allow ing to present a consolid ated set o f various facts, su p p o rted by the em pirical results. H ow ever, a suitable clarification o f those results is required, in w hich the th eo ry should be expressed in accordance to them - giving a possibility to conclude a certain n atu re o f predictions an d to co m p are th a t w ith the results. Such an ap p ro ach to the th eo ry does n o t com ply w ith the n o tio n o f simulation, either.

It is supposed th a t the sim ulation can be looked a t from two different angles. Since the sim ulation bases on m odelling o f a given fragment o f reality, the o b tain ed results an d descriptions are kind o f a theoretical ap p ro ach to their p ro to ty p es. T h a t is w hy, a language o f the sim ulation is a first-lev el-lan g u ag e, called an objective language. A t the sam e tim e, the sim ulation m odels them selves can be a subject to research, certainly in a seco n d -lev el-lan g u ag e, called a m e­ ta-language. Such a m e ta -la n g u a g e can be a System T heory language, a Set T heory language, a C ybernetics’ language o r any other language. Y o u can find tho se kinds o f ap p ro ach es in various publications.

From a practical p o in t o f view, the sim ulation is equally treated with other scientific m ethods. A bove all, it is seen as a m eth o d having a very im p o rta n t stage o f verification.

To sum up, the subjects considered an d presented above, co n stitu te just a sector o f a huge area to be faced by the p h iloso ph ers w ho intend to undertake deeper analysis o f the n o tio n o f sim ulation. All issues related to the prob lem o f sim ulation fascination w ith the sim ulation method, its im p ro p er use o r trea tin g a h u m an being as a subject o r object o f the sim ulation process itself - seem to be the m ost interesting ones.

BIBLIOGRAFIA

Bekey G . A., M odels and reality: som e reflections on the art and science

o f sim ulation, S im ulation, 29(1977)5, 161-164.

B enham R .D ., (M onte), Sim ulation: one m a n ’s view o f p ast, present

and fu tu re , Sim ulation, 29(1977)5, 186-187.

Bunge M ., Analogy, simulation, representation, R evue In tern atio n ale de P hilo sophiae, 23(1969), 16-33.

C olby K .M ., W a tt J., G ilb ert J.P ., A com puter m ethod o f psycho­

therapy, Jo u rn a l o f N e rv o u s and M ental D iseases, (1966) 142,

148-152.

F ra n ta W .R ., The process view simulation operating and program m ing

system s, New Y ork 1972.

H aney M c R ., C om puter simulation. A pfracticalperspective, L on do n 1991.

H eller M ., Filozofia nauki. W prowadzenie, K rak ó w 1992. H ingsto n R .W ., Instinct and intelligence, New Y o rk 1992.

K een R .E ., Spain J.D ., C om puter simulation in biology. A basic

Introduction, N ew Y o rk 1992.

Lataw iec A ., Pojęcie sym ulacji i je j użyteczność naukowa, W arszaw a 1993.

L ubański M ., Z zagadnień symulacji, S tudia Phil. C hrist. 12(1976)1, 101- 112.

N a y lo r Т .Н ., C om puter sim ulation techniques, N ew Y o rk -L o n d o n 1966.

N oris A ., On defining the sim ulation process, S im ulation 13(1969)10, 199-200.

P idd M ., C om puter simulation in m anagem ent science, C hichester, N ew Y ork 1992.

S h an n o n R .E ., S ystem s simulation: the art and the science, N ew Jersey 1975.