Many definitions of simulation in research
literature are quite technical, i.e. associated with
creating different simulations with the means of computers
(e.g., Zeigler et. al. 2000), or alternatively, they are
philosophical in nature, drawing from critical theory and
the social sciences (see Cubitt 2001). Encyclopædia
Britannica Online offers the following definition:
[…]
in industry, science, and education, a research or teaching
technique that reproduces actual events and processes under
test conditions. Developing a simulation is often a
highly complex mathematical process.
For the purposes of this paper, a definition
that helps us to understand the aesthetics of simulations is
necessary. The definition has to take note of uses of
simulation for entertainment purposes – i.e. not only
reproducing or modeling actual events but also creating
make-believe worlds. Definitions with similar premises have
been hard to find, but we will refer to a pair of them in
what follows.
Cathy Stein Greenblat has written about
designing games and simulations for pedagogic purposes. The
simulations created and proposed by Greenblat are not
computer-mediated but mostly board games and role play
scenarios with a simulative logic. Greenblat (1988, 14)
defines simulation: ”A simulation is an operating model
of central features or elements of a real or proposed
system, process, or environment.” Greenblat emphasizes
certain critical dimensions of simulations: first,
simulation is a dynamic model, second, only
selected elements of the referent system are
included, and finally, that there can be several
different sorts of referent systems (ibid.).
Gonzalo Frasca, games scholar and
ludologist, has promoted simulation theory in relation to
games. He pursues the notion of ‘simiotics’. It
presents an applied form of semiotics for the purposes of
understanding how simulations work, produce meaning, and are
interpreted.
Whereas Frasca applies Peirce’s triadic
model of the sign to pursue a simiotic model, my interest is
in studying how different gameplay elements (interfaces,
audiovisual elements, representations, rules, etc.) combine
to produce simulations, and how do those elements and their
relationship to each other make one simulation
formally different from another. This is an interest
for knowledge that is essentially design-driven.
Frasca’s definition of simulation is a
result of rethinking previous, technology-based definitions
employed in, e.g., research into computer graphics. He wants
to broaden the notion of simulation from computer-based
simulations to non-electronic devices such as toys. Computer simulation is the primary
method that has been used to study the modeling of systems
(Frasca 2001a, 24), as computers can be employed “to explore
mathematical models of structures and processes”
(Greenblat 1988, 18.). Computer simulation has been defined as
“the use of a computer to represent the dynamic
responses of one system by the behavior of another system
modeled after it.”
Frasca adopts the notion of system from
cybernetics, where different systems have been
scientifically simulated in order to predict their behavior.
He builds his definition on the notion of
‘system’, as it is defined and used in the study
of cybernetic systems. System is understood as “a set or arrangement of entities
so related or connected so as to form a unity or organic
whole”.
Adapting this definition
of system has the advantage that it encompasses the
different ‘processes’ and ‘environments’
that were mentioned in Greenblat’s definition.
Frasca also refers to similar approaches in
studying the aesthetics of electronic texts, particularly
Espen Aarseth’s studies on cybertexts that operate in a
triad of operator, verbal sign, and medium (Aarseth 1997,
21). Frasca states his premise as follows:
Since both videogames, non-electronic games and toys can be
separately understood as “a set or arrangement of
entities so related or connected so as to form a unity or
organic whole” […] I
propose to use simulation theory to analyze these games as
simulations, in order to understand how they work and,
particularly, how players interpret its content. (Frasca
2001a, 24.)
Frasca formulates his definition of
simulation around the goal of modeling the behavior of a
particular system to a certain extent:
“to
simulate is to model a (source) system through a different
system which maintains to somebody some of the behaviors of
the original system”. The key term here is
“behavior”. Simulation does not simply retain the
– generally audiovisual– characteristics of the
object but it also includes a model of its behaviors. This
model reacts to certain stimuli (input data, pushing
buttons, joystick movements), according to a set of
conditions. (Frasca 2001b.)
I will name the source system, i.e. the
object of simulation, as A (cf. ibid). The resulting model,
i.e. a particular instance of simulation, is named B. It is
useful to think the relation of the model to the source
system as a circle located within a larger one (see figure 1
below). The large circle represents A. If one reduces B, the
smaller circle, from A, the result of the equation points
out the features of the source system that have been left
out or simplified in the simulation (B). This relationship
will be illustrated in more detail later. [Figure1]
Simulation/game?
So, when is a simulation not a game? This
question needs to be answered in order to avoid
terminological confusion. Frasca (2003) writes: “The
key trait of simulational media is that it relies on rules:
rules that can be manipulated, accepted, rejected and even
contested.” Frasca leads us to believe that both games
and simulations have rules. But there is a difference
between SimCity and a simulation tool used by city
planners, surely? The rules must have different functions in
simulations intended for other purposes than gaming?
Greenblat (1988, 14) writes about the
specificity of game-simulations: ”The term game
is applied to those simulations that work wholly or partly
on the basis of players’ decisions.” She goes on
to describe gaming simulations that incorporate
characteristics of games, such as roles, goals, constraints
and payoffs. Greenblat finishes with the following
statement: ”Gaming-simulation, then is a hybrid
form, involving the performance of game activities in
simulated contexts.” (Ibid. 14-15.)
Another aspect that Greenblat discusses is
the distinction between role playing and gaming-simulation.
She argues:
Role
playing is an element of gaming-simulations, but the
latter also include other components. In most role-playing
exercises the participant is assigned a role and given the
general outline of a situation; from there the action is
freewheeling. In gaming-simulations, on the other hand,
roles are defined in interacting systems. That is,
emphasis is on the role as it interacts with other roles;
the model creates the basis for the dynamic interaction, and
includes the constraints, rewards, and punishments referred
to above. (ibid, 15.).
The latter half of the cited passage
actually describes quite accurately what happens in
role-playing games (both so-called table-top and
live-action role-playing games), where it is the game master
that governs the interaction (possibly with the help of a
rule book) by giving out challenges, rewards, punishments,
and so on. The point here is that when thinking about role
play in relation to simulation, it is necessary to make a
distinction between role-playing games and role-playing
exercises.
Overall, Greenblat’s discussion is
useful for our purposes but does not provide entirely
satisfactory answers, because it is clearly bound by her
premise of creating simulations that, on one hand, have
references in reality, and on the other hand, serve mainly
pedagogical purposes.
Although these aspects do not run contrary
to current forms of digital games, they do not exhaustively
cover the field either. In many games designed for fun and
entertainment, the whole point is that the reference system
is entirely fictional, a make-believe fantasy world, for
instance. Any learning that takes place while playing the
game is either related to the game itself (rules, general
accumulation of skill and knowledge) or secondary in
relation to the primary purpose, i.e. entertainment.
Frasca explains the difference between games
and other simulations with the help of Roger Caillois’
(1961, 13–14) distinction between paidia and
ludus, the different nature of ’play’ and
’game’. Basically paidia refers to spontaneous
forms of play, where there exist few rules or they can be
changed, whereas ludus refers to the more inherently
game-like structure with clear goals and pre-determined
rules.
Frasca argues that simulations structured
with ludus rules follow a binary logic
(winning/losing) that is suited for traditional game
structures, whereas simulations with paidia logic
have potential to illustrate more complex relations and
processes, such as human relationships. However, in this
process, the latter become other kinds of simulations rather
than simulations structured as games. (Frasca 2003.) We will
return to Frasca’s typology of simulation rules later.
So, clearly every simulation is not a game.
Games, with their rules, are one particular way of creating
a structure for simulation (cf. Ibid.). Therefore it is
justifiable to discuss certain kinds of simulations as
games. I will use the term ‘game-simulation’ when
I want to emphasize the fact that a particular simulation is
structured according to ludus.
But does every game have some simulative
characteristics? Is Tetris or Solitaire a
simulation, and if so, what are their referent systems? Are
some games more relevant to discuss from the perspective of
simulation than others? Probably yes. We can begin to answer
this question by looking at games’ tendency to create a
system or transform an existing one for gameplay purposes.
After that, we will move on to deconstructing
game-simulations in order to understand how they produce the
behavior of a system.
Real vs. make-believe referent systems
Frasca (2001a, 25) points out that a
‘real-systems premise’ has been the dominant
method of implementing computer simulations and theorizing
about them as well. He suggests that the reason is
historical: simulations have had their roots in scientific,
mathematical experiments. With the emergence of computers as
entertainment medium, and digital games as one particular
form of computer-mediated entertainment, they present
possibilities for simulating systems that ”that do not
exist or even contradict the rules of physics of our
universe.” (Ibid.)
Frasca continues with an important point
that also illustrates what ’simiotics’ essentially
is in relation to semiotics:
To claim that there is a need for a real referent in
simulations is similar to say that the word unicorn
is not a sign since its referent is not real. Therefore,
I will apply the term “simulation” to the
representation of processes that mimic a system by the
behavior of another, even if its source system is not real. (Ibid., 25-26)
My premise will be the same. Following it,
Tetris has simulative characteristics, as it creates
a system that behaves according to certain rules. A computer
version of Solitaire simulates the card game; in
other words, it has a system referent that is real.
Whether the simulation refers to real,
actual system(s) or not, there is also the questions of
interpretation, previous knowledge of games, and a larger
cultural context. In order to interpret a game simulation as
one, the player who engages with the simulation has to
interpret the rules as the ‘simauthor’ (Frasca
2003) intended them to be interpreted. Frasca gives an
example how a simulation can be misinterpreted, or not taken
full advantage of, if the referent system is not known in
detail: a player who does not recognize that the archaic and
highly abstract video game Pong (Atari, 1972)
simulates table tennis, might not understand the game or
simulation at all (Frasca 2001a, 30-32). On the same topic,
Karen Carr (1995, 6) writes: “[…] a
simulation is a pretence which depends upon interpretation
by a person who is familiar with the rules of
representation.”
In digital games, the player gets to
manipulate objects, and thus the course of events. Therefore
objects in a game have to be represented in a way that the
player can realize that s/he is able to interact with them.
The concept of ‘affordance’, originating from J.J.
Gibson’s studies in perceptual psychology, is worth of
note here (see, e.g., Gibson 1977). It refers to the
observer’s understanding of what an object allows her
to do; what it affords, so to speak. When designing
game-simulations, it is not only necessary to both constrain
and guide the player with rules, but also craft
representations with affordances so that the player
understands how to invest her effort into the game. Objects
should not only look and sound coherent, but behave
coherently, and according to the players’ expectations.
But then again, it is the nature and power
of games to reverse real-world causalities and
behaviors. This has to do with the general make-believe
nature of many games, and especially forms of play. Often
when playing, people transform the nature of the playing
environment for the purposes of playing: a domestic room
becomes a doctor’s office, a playground becomes a
battlefield, and so on. This effect has been described as
the ‘second-order reality’ of play and games
(Caillois 1961, 8). Everyone who accepts this pretence for
some duration is ‘playing along’. Digital games,
when they simulate make-believe worlds, rely on this same
pact between the game and the player, which is essentially
about understanding and accepting the rules of the game.
In this sense, I argue that games are less
open to different interpretations than media representations
in general, as they are formal systems that need to be
operated by the player in order to make sense as
games. This does not mean that the role of the player is
somehow diminished, but quite the contrary, as both
interpreting rules and gameplay structures and playing
within the constraints and possibilities they produce
require active participation in the simulation.
On these grounds, I define games’
relationship to simulations as follows: Games are
simulations that allow a player or players to influence the
behavior of the modeled system in the context of pre-defined
rules.
The three reference points of simulation:
system, representation, and interface
In the following, I will present a model
with which we can think how different games’ simulative
elements function in relation to each other. In the model,
three reference axis of simulation are added into the
previous figure. Each axis presents one aspect of the
referent system. The model is based on the idea that
simulation operates between three nodes:
1.
System:
the behavior of the referent system (A, ‘the organic
whole’) of simulation.
2. Representation: the sign layer that represents the system with (animated)
images and sounds.
3. Interface: the input schema
that gives the player access to the system via
representation, and henceforth access to the simulation
itself.
We need a model that illustrates the
relation of A to B and the degree of simulation implemented
into each node. To give an example, if A is football, we
need an investigative model that we can 1) for the purposes
of analysis, apply to any football game (Bx) that
simulates the sport, and 2) for the purposes of designing
simulations, to help in thinking how to select the elements
to be simulated, their relation to each other, and their
implementation.
The following model in Figure
B is essentially
about deconstructing simulations. It allows us to map a
particular game into it according to how the three elements
are simulated:
The referent axes, sectors and simulational
rules
Let us look at the model in more detail.
Each node has an axis that leads from B to A. The axes’
function is to indicate the variation of detail in a
particular instance of simulation. System, representation
and interface present three vantage points with which to
carry out analysis between different games.
The relationship of each axis to each other
is not constant, because in some games the system,
interface, and representation function in closer relation to
each other than in others. For example, in strategy games
(such as different sports fantasy leagues) that are based on
controlling different resources via mostly numeric
interface, the system and the interface are almost the same,
and the representation is bent on numerical representation.
In quite a different subgenre of games, the
First-Person Shooter, the system (usually a fantastic
world), the representation (a detailed three-dimensional
world), and interface (controlling the subjective point of
perception as if ‘being’ the player) are very
closely connected to each other. The game-world might have a
real-world referent, or a counterpart familiar from other
forms of fiction (e.g., as with game adaptations of films).
The length of each axis depends on the degree of behavior
implemented in the simulation as opposed to a representation
of the system, where it is impossible to include the
behavior in any dynamic way.
Let us look at the different sectors between
the axes. The sectors include elements of game-simulations
that work between two axes. In the sector between
representation and interface there are the basic audiovisual
elements that function in relation to the player and her
concrete means to affect them via the interface. The
so-called dimensionality, point of perception, and
soundscape and other audiovisual elements (see Järvinen
2002) operate between interface and representation.
These structures are the plain, wire-frame
building blocks of the audiovisuality of a particular game.
They are topped with representations, which operate in
another sector, the one between system and representation.
In the sector between system and interface, there resides
the means of manipulating the behavior of the system. These
work hand in hand with the gameplay structures. The latter
define the causal relationships, criteria of success, and
possible rewards and punishments of the player’s
actions.
Rules
The rules of simulation operate along the
different axes, and through their interrelations. Frasca
distinguishes three levels of rules that affect the nature
of the simulation and the ideology it conveys through causal
and representational means. The first has to do with
representation, especially how characters, objects, etc. are
represented. The second are what Frasca calls manipulation
rules: “what the player is able to do within the
model”. The third level is the goal rules: “what
the player must do in order to win”. (Frasca 2003.)
These rules each map to the different
sectors that reside between the system, interface, and
representation axis. This varies across different games and
genres. For instance, when the goal rules state that there
is a certain amount of skill involved in winning, and this
has to do with a thorough knowledge and execution of the
control schema (e.g., in a skateboarding game), the goal
rules function in close connection to the interface axis.
They might be indistinguishable from the manipulation rules
altogether. In case of a game that is more focused on
understanding certain causal relationships the goal rules
function in closer connection with both the representation
and system axes. Examples abound in the strategy game genre
where understanding the logic and interrelations of
resources are keys to winning. In games where narrative
sequences, with their causal logic, are used for giving the
player information regarding solving the game’s tasks,
this is the case as well.
System
axis
The system axis points out how accurately
the general behavior of the referent system is simulated. In
games this behavior is governed by rules and the actions of
players within those rules. In case of a football game,
then, the axis indicates in how detailed fashion are the
official rules of football implemented into the simulation,
and also, how detailed is the simulation regarding the
physical behavior of human body in the context of playing
football. Different institutions and structures (leagues and
competitions in the football example) can be included in the
simulation. These elements sum up the length of the axis.
The distance between B and A depends on the
complexity of the system. For game purposes, then, the axis
might end up quite short, as numerous traits of the system
are either omitted or simplified. This does not necessarily
produce a simple, or a ‘bad’ game. Often the
degree of simplification has to do with interface issues: it
is not possible to map a highly complex system, and means to
manipulate it, to such a control device as the present
console gamepads, for instance. These kinds of limitations
have usually been solved by design solutions where a simple
press of button is programmed to execute a number of
behaviors in the system. This is often the case in
game-simulations such as the SimCity or The
Sims, where complex processes (e.g., the construction of
buildings, or social interactions) are automated once the
player has ‘pushed’ them into motion.
Representation
axis
The representation axis tells us about the
game’s audiovisual representation: it runs from
absolute photorealism and aural recreation of a particular
soundscape to simplified abstractionism (the football
equivalent of Pong, to keep with the same example).
In highly abstract games, such as Tetris or
Othello, there is virtually no representation
at work. The tetraminoes in Tetris and the pieces in
Othello do not represent anything but themselves as
tokens of the game’s rules. The fact that a deck of
cards has rooks, queens, and kings, is one step towards
representation. However, a deck of cards is a game system
that could be represented with other means and symbols as
well (and there are numerous examples of this).
To sum this up: regarding digital games, the
more photorealistic the game’s audiovisual style is,
the more relevant is the question concerning politics of
representation.
The representation axis has particular
relevance for thinking about the relationship of simulations
and digital games, especially when one thinks about the
dominating trend of three-dimensional graphics and sound in
games from the mid-1990s onwards. In an article on the
‘virtual realism’ of different virtual reality
applications, Christou and Parker (1995, 67) write: “In
pictorial art, the brush strokes and markings are placed on
the canvas in order to mimic the visual product of the
projection of light. In three-dimensional computer graphics,
the light projection process itself is simulated.” This
kind of notion about increased realism in computer graphics
through simulation is somewhat technology-driven pursuit,
which has dominated game production. It is only lately that
pictorial forms of representation have become popular, or
even trendy (the ‘cel-shading’ movement apparent
in games like Legend of Zelda: the Wind Waker,
Nintendo 2003)), in creating audiovisual outlook for digital
games.
The means of representation a particular
game employs are in close connection with both the interface
and system, but this varies between and within game genres.
The representation, or a specific element in the
audiovisuality of a game, can dictate the choice of
interface. A completely textual representation, as in the
numerous text adventure games of the 1980s, meant that the
interface took the form of a text parser and participation
in the simulation was conducted by typing commands (in a
specific syntax) from the keyboard. Then again, by placing
the point of perception as first person, the FPS games led
to the development of interfaces that try to fuse the
interface logic to the first person viewpoint as
‘naturally’ as possible in order to pursue the
illusion of non-mediated game experience.
Interface
axis
The interface axis points out the complexity
of the control scheme and its accuracy or complexity in
relation to the actual physical experience of playing
football or the fictional experience of piloting a
spaceship, for instance. For game simulation purposes, often
a highly simplified control schema is relevant for the sake
of playability, as, e.g., in Virtua Tennis (Sega,
2000) where only two buttons are used for different strokes.
The complexity or simplicity of control schema has been
discussed under the concept of orthogonality (Dietrich
2002). I will employ high versus low degrees of
orthogonality as the continuum that runs along the interface
axis.
The
journey from B to A
The simulation, B , operates in the
interconnection of the axes. The referent system is a
superstructure that is basically a sum of the axes as they
would present the actual, 100 percent implementation of the
referent system. The generic model is applied to practice by
evaluating the length of each axis, and mapping and
analyzing what resides in each sector (in between two axes)
in a particular game.
Simulating media representations: Grand
Theft Auto
Grand Theft Auto
is a series of games (by RockStar Games, 1996–2002)
focused around criminal underworld, drawing its influences
from hard-boiled crime fiction. The games consist of
different missions where the player controls a character
whose job is to carry out a task of one sort or another
(often a crime such as bank robbery or assassination, or
working as a bodyguard or chauffeur). The series third part,
Grand Theft Auto III (2001, henceforth GTAIII)
was immensely popular and was handed many awards for its
innovative game design. Grand Theft Auto: Vice City
is (at the time of writing) the most recent sequel, building
on the innovations and success of GTAIII.
The two latest
installments in the series are particularly fruitful to
study from the perspective of game-simulation theory.
GTAIII’s important difference to the first two
games was that it set its gameplay into a detailed
simulation of an urban environment (called ‘Liberty
City’ in the game). Technically and
representation-wise, the change became apparent as a shift
from a two-dimensional, top-down presentation to a
seamlessly three-dimensional, detailed audiovisual
environment.
In the context of this
paper, GTAIII essentially presented a change in the
detail, degree and referent system(s) of its simulation. Not
only did the system, representation, and interface axis
change in orientation, but their relationship and reference
points changed, too. The complexity of the referent system
was increased as many more behaviors of urban environments,
vehicles, weapons, etc., were incorporated to the game. On
the sector of representation, another dimension was added
quite literally. Consequently, the interface had to be
adapted for the requirements posed by the modifications.
Vice City
(henceforth VC) brings another layer to the
simulation. Instead of intertextual references to popular
culture and crime fiction on a general level, as in
GTAIII, in VC RockStar Games has tried to
recreate a city of a certain era by using numerous
pop-cultural elements in crafting the simulation. For
instance, the game has an extensive soundtrack of 1980s pop
music, and simulation-wise, the most important feature is
that they are mostly played through the radio stations
within the system, not as so-called off-game-world sound
that functions in similar fashion as non-diegetic film sound
to provide different atmosphere. The radio stations are part
of the referent system that VC is a simulation of.
However, as with any game-simulation, the choice of songs
presents an interpretation of what 1980s popular music is
and sounds like.
This dimension of
interpretation is an important difference between
simulations crafted for scientific and entertainment
purposes. For instance, every sports game-simulation is an
interpretation of the sport rather than universally
generalized model built out of the dynamics of a particular
sport.
What makes VC
particularly interesting is its relation to representation.
The referent system is not so much a time period of the
1980s in a city somewhere in the United States, but the
crime-flavored representations that we know from fictional
detective TV series, comics, gangster films, and so on.
Despite the more obvious references to the TV series
Miami Vice, for instance, the overall BVice
City is a pastiche of numerous elements. These
intertextual elements operate within the domain of
simulation, but also within the ones of representation and
narrative (especially during the cut-scenes).
Grand Theft
Auto: Vice City as game-simulation
Next, we will study
VC’s elements of simulation and apply the generic model
to its analysis. Basically the referent system of VC
is a sum of an environment of urban crime, with a distinct
style of a certain era, and a collection of conventions from
crime fiction (scenarios, character stereotypes, etc.).
These constitute the intertextual references and genre
characteristics of the game. The voice acting of different
characters, with numerous well-known actors behind the
voices (actor Ray Liotta provides the voice for the
player’s character Tommy Vercetti) is another
noteworthy aspect of the game. Genre-wise, the voice acting
plays a considerable part. Strictly speaking, because
Vice City is not a direct adaptation of an existing
fictional universe (such as the TV series Miami Vice), all
the elements (the soundtracks, voice-acting, missions, etc.)
do not produce a game-simulation of 1980s crime fiction, but
an interpretation of 1980s crime fiction in the form of a
game-simulation.
The conclusion is that
VC’s referent system is not as easily recognizable as
with game adaptations of films and television series or
sports, for that matter. With games like Enter the
Matrix (Shiny Entertainment, 2003) or NH2K3 (Sega, 2002)
the referent systems – the fictional universe of the
film series and ice hockey in the National Hockey League as
televised by ESPN sports – are unambiguous.
Rather than having an unambiguous referent system, VC
substitutes it with a more general theme that is influenced
by numerous phenomena of popular culture.
This has to do with
the politics of representation in Vice City. It
clearly operates in a particular domain of irony and parody
with its retroish pop-sensibility. ”Vice City is
the first nostalgia sim”, as Wagner James Au (2002)
wrote in a Salon.com article. Its particular
blend of nostalgia and parody brings us back to the
relationship of the underlying game system and its
representation (the deck of cards example, above). Actually,
with its three-dimensional graphics engine, character and
object models, and gameplay structures, GTAIII
produced a game system that VC is built upon. This
observation shifts the focus on VC’s particular
means and politics of representation.
A more thorough
analysis would focus on the notion of parody and how it is
employed in VC. There is no space to analyze it here,
but let us point out some directions for ideological
analysis of this particular simulation: Questions to ask
this particular game-simulation include: Does parody as a
rhetorical technique reinforce what it parodies? Is parody
used in VC as a scapegoat for sexism – does VC,
by reintroducing a typical masculine character familiar from
1980s crime fiction, actually reinforce this type of
masculinity? Do the manipulation rules and the causalities
implemented through them into the game resist or invite this
kind of interpretation?
In a game that is built around conveying a
certain atmosphere, the audiovisual means to create the
simulation are important. VC embodies so-called
caricaturistic style (see Järvinen 2002) with
three-dimensional game environment and third-person point of
perception as its core audiovisual elements. The animation
of characters and objects (vehicles etc.) is somewhat
stylized, with conventions of popular fiction as reference
points. Thus, their sets of behaviors are modeled according
to familiar stereotypes (mafiosos, rock stars, femme
fatales, etc.). As a simulation, VC does not aim for
100 percent accuracy of real-life behavior. Rather, its
elements of simulation are in line with its general,
nostalgic sensibility. Narrative cut-scenes are used to
inform the player about the background story of the game and
to motivate the missions given to her. They relate to the
bottom sector (representation–interface) in the sense
that they interrupt the gameplay and prevent the player from
accessing the simulation, thus shifting the focus
momentarily from the simulational to the representational
domain. - In the Figure
C, elements of
simulation in VC are mapped into the general model.
As with GTAIII,
‘Vice City’ the city lives and breathes in a
complex way independent of the player’s efforts: the
sun rises and sets, traffic operates, and so on. In other
words, urban behavior is simulated to quite a high degree,
but the manipulation rules and means to take actions that
the rules govern are located on street-level – as
opposed to the ‘high’ level manipulation of
SimCity, for example.
The gameplay
functionalities are implemented according to this approach.
They are simple actions: the player can walk, run, drive
different vehicles (cars, motorcycles, boats, helicopter),
fight, and operate different weapons (from baseball bat to
guns).
Essentially, these are
tools given to the player to play the game. The use and
behavior of each tool is simulated in a simplified manner,
and following similar interface logic: the control pad is
used in aiming a weapon or steering a vehicle, and the tool
is operated (shot, accelerated, etc.) with the press of a
single button on the gamepad. Tasks such as reloading
ammunition, changing gears, etc. are made trivial in the
sense that they are automated. These methods of
simplification are the steps that differentiate B from A,
and most importantly, make it playable.
The manipulation
rules, i.e. “what the player is
able to do within the model”, are materialized as the
gameplay functionalities discussed above. In VC, the
manipulation rules regarding different vehicles are also
important, as interacting with these types of tools makes up
a considerable amount of playing the game. Even though the
driving models are simplified when compared to such
‘real driving simulators’ as the Gran
Turismo (Konami 1997–) game series, still, a car in
VC behaves like a car, and can be wrecked like a car.
Affordances and rule hierarchies of Vice
City
In order to thoroughly uncover how VC
operates as a simulation, a detailed analysis of the
different causal gameplay structure would be needed. This
kind of deconstruction, where the details of the simulation
are analyzed, sheds light on how the system is designed to
behave in response to the player’s actions.
This has to do, on one hand, with the
coherence of the simulation: if a single character in
VC can be killed, then the possibility of death
should apply to any character; if one building can be
entered, then all buildings should be enter-able. We
return to the concept of affordance. In practice, as games
are about rules, the rules often serve to constrain the
players in this sense as well: only the buildings that are
relevant in order to progress in the game, can be entered,
and so on. The less simulative a game is, the more of these
kinds of constraints it is bound to have. The use of
narrated cut-scenes is one example, employed in VC as well,
that divorces the player momentarily from the simulation and
its particular rules. More and more, however, we are
beginning to see examples of games that simulate very
complex systems, and in an increasingly coherent manner. The
development of the GTA series presents one particular
trend in this direction, while Will Wright’s Sim-games
present another approach (see Wright 2003).
On the other hand, analyzing the causalities
of actions within the simulation produces observations about
the politics and rhetorics of a particular simulation. The
key question here regarding analysis is, whether the
simulation rules can truly be contested, as Frasca (2003)
claims of simulations in general, or not. If not, it is
likely that the game includes elements that are not
simulative, such as narration. This is the case in VC
but still, it does convey meanings with its simulative logic
as well. Even though this makes different solutions to the
game’s challenges possible, they take the form of
missions, i.e. specific tasks within the system, and the
player cannot contest their purposes and goals, and the
means to achieve them. It is Frasca’s category of goal
rules that governs these aspects.
However, there is a certain hierarchy to the
manipulation rules: if the player does not want to pursue
the missions, s/he can choose to take control of a taxi (or
an ambulance, for instance) and start earning money
transporting passengers around Vice City. This presents a
paidia-orientated approach to the game. If, however,
she takes on a mission, she has to pass it in order to keep
playing the game. This, on the other hand, is a goal rule
shaped according to ludus logic. Completing the game
requires the player to pass a number of these subtasks. This
means that in VC, as with majority of games, the
manipulation rules are ultimately subordinated to goal
rules.
Despite the brevity of the analysis
presented here, these arguments help to understand
VC’s particular techniques of balancing
simulation and game elements, and the potential methods of
conveying meanings that are characteristic to the two.
To give a comparative example: Another
recent game, Legend of Zelda: The Wind Waker
(Nintendo, 2003), presents the player with a massive
fantasy world, which has numerous simulative elements, such
as a vast sea that simulates a system, ‘an organic
whole’, that is easily recognizable and behaves
accordingly. However, this particular game-simulation has
quite many incoherencies between the different sub-systems
it simulates, and there are frequent narrative sequences,
which prevent the player from contesting any of the rules,
both those governing the simulation and the ones conducting
progress in the game. Both manipulation rules and goal rules
are less flexible than in VC. This does not
necessarily mean that one of the two games is better than
the other, but rather that they both employ elements of
simulation with different balances and emphasis between
system, representation and interface.
From system to theme: the ethics of popular
simulations
Whoever
designs a strike simulator that is extremely hard to play is
describing his beliefs regarding social mechanics through
the game’s rules rather than through events. (Frasca
2003)
The quotation from Frasca brings us to the
politics and ethics of simulation. These have not been the
focus of the theory presented here. Still, it is important
to recognize the fact that all game-simulations are
interpreted and played in specific cultural contexts. This
is when the formal elements analyzed here enter the domain
of play and gaming, and give birth to informal experiences
and interpretations. Although the resulting reasoning or
emotions can not be thoroughly anticipated, I argue that
deconstructing simulations allows us to both produce
readings of their ethics and politics, and point out methods
to design future simulations with specific political and
ethical premises.
Increasing the degree of simulation means
increasing complexity as the referent systems get
multiplied. For instance, the elements of simulation in the
beach volleyball game Dead or Alive: Xtreme
Volleyball (Tecmo, 2002) have various referent systems:
most visibly volleyball, the female body, dating, and a
casino house. With simulational methods, the game conveys
potentially quite different meanings and beliefs than the
strike simulator that Frasca imagines. The fact that the
game is quite easy adds to this impression.
The volleyball game example serves the point
of illustrating the tendency of digital games to
‘disguise’ the referent systems under a specific
game theme. Whereas the referent systems, or their
combination, functions as the context of the behaviors in
the simulation, the theme functions as the context of the
meanings that the simulation produces. A simulation that
simulates the behavior of atoms does not have any other
theme than the atoms themselves. In game-simulations,
system, representation and interface co-operate in the
context of a theme in order to produce complex set
experiences and meanings that accompany them.