Formal
Abstract Design Tools
In
the lecture preceding Doug Church's, Marc LeBlanc sought out a different
approach to game design. Under the label of Formal
Abstract Design Tools (FADT), LeBlanc, Church and others are trying
to establish rules, models, techniques and, most importantly, a shared
vocabulary to improve the understanding of game design as a craft. The
ideal FADT, according to definition, is "well-defined," "abstract"
(i.e., applicable across genres), has day-to-day utility, and works
in a well-understood application context. During another GDC discussion,
Warren Spector pointed out the unexpected resistance game designers
exhibit when facing the idea that their work and thinking could possibly
be described and discussed in more formal ways, and Marc LeBlanc was
quick to pre-empt concerns by assuring that FADTs are not meant to be
a "Swiss Army Knife" of game design.
His
presentation started with the battle cry "down with fun,"
which he elaborated upon as he created a taxonomy of "fun"
to illustrate both the fuzziness of the concept and its limited applicability.
"Fun" as applied to games covers everything from simple sensual
pleasure to make-believe, from drama to the satisfaction of solving
intellectual challenges, from social interaction to submission,
from exploration of another person's invention to self-discovery. It
is hard to find precision in such versatility.
Personally,
I suspect that a good share of the FADT efforts are trying to reinvent
the wheel. The problems and challenges in finding a common vocabulary
for a craft have been encountered in other professions, and the recent
decade has brought a variety of solutions. In my limited experience,
Christopher Alexander's work on "design patterns" seems the
most promising avenue (more about this in a upcoming Gamasutra article),
which uses an approach that has been successfully applied to fields
as diverse as architecture, workflow management, and software engineering.
(You can also see Zach Simpson's collection of game
programming patterns as an example.)
Marc
LeBlanc also looks to other disciplines for inspiration. In his GDC
talk last year, he introduced feedback loops as a design concept. This
year he ventured into "complex systems," which quite naturally
contain feedback loops: the rules governing the state change take the
current state into account. "Complex systems" (much like "fractals,"
"nonlinear dynamics," or "emergence") has become
a popular science buzzword over the past decade, and the concept has
suffered from this. Marc LeBlanc focused on the observation that the
behavior of a dynamic system often cannot be easily predicted from its
set of rules, even if those rules are deceptively simple. In reverse,
mere observation of a sample system
will not allow you to deduce of those rules.
The
example commonly used to illustrate complex systems and their dynamics
is that of cellular automata (for a reference I suggest
Steve
Wolfram's book). The most popular of the cellular automata is John
H. Conway's Game
of Life, which LeBlanc used to demonstrate properties "emerging"
from a set of rules. He then compared this 2D cellular automaton with
2D board games like Chess or Go, where attack and defense tactics and
strategy are only implied by the game's rules. He also pointed to card
combos in Magic: The Gathering and emergent properties like Trains,
Kiting, and Killstealing in EverQuest (the latter makes emergent
properties look more like a problem than an asset).
LeBlanc
tried to make a case for emergent complexity as a possible source for
"fun." In his view, such emergence creates larger spaces to
explore, offering the player more features to discover and more challenges
to meet. He tried to distinguish systems with simple elements from those
in which the constituents are quite complex . The one word he did not
use was "combinatorial" – a good deal of the complexity in
cellular automata is due to the fact that, while the number
of possible states per cell is finite, the number of cells is quite
large, and the resulting state space of the entire system is blown up
beyond human comprehension by combinatorial explosion.
There
is little to be learned from cellular automata that could be applied
to game design, thus his presentation quickly moved on to examples such
as sports simulations, which are well advised to replicate emergent
properties of the real world by replicating the underlying dynamics.
(Ted Zuvich's GDC lecture on physically accurate vehicle dynamics for
Need For Speed was a case in point). For most games, differential
equations will rule the player's world, not the discrete counting rules
of transition that govern cellular automata. On another level, The
Game of Life is indeed a telling metaphor with respect to game design:
one detail LeBlanc did not elaborate on was that they are fully deterministic
systems, ticking away like clockwork, driven solely by the laws of behavior
and the initial conditions as defined by their design. If
game designers ever get serious about abdicating authorship, these two
devices -- initial conditions and laws of dynamics -- will be the essence
of the tools left at their disposal. Random initial conditions,
as contemplated by LeBlanc, will deprive the designer of even the ability
to set the stage, before leaving it for good.
The
lecture made the point that complexity is not accomplished by creating
lots of rules. In fact, the common way to implement a game simulation
is to write an expert system -- a database of rules of thumb and special
cases, patched and hacked to accomodate short-term needs during game
development. The properties created by rule-based simulations don't
always make sense, and might even be contradictory. On
the other hand, properties emerging from perfectly consistent simulations
usually come as an unpleasant surprise. For instance, once players discovered
rocket jumping in Quake 2 (whereby players fire the the
rocket launcher at the floor and use the reactive force to propel themselves
skyward), they began to use that trick to cut corners in ways the map
designers had not anticipated. Warren Spector gave another example in
a recent interview about his game, Deus Ex. He explained that
the interplay between the game's AI and the sound caused by a single
bullet casing hitting the ground exposed sniping players to such a degree
that, in the interest of preserving the plot, the game simulation was
hacked to accommodate this emergent property. (Caseless ammunition was
seemingly not an option).
Marc
LeBlanc pointed out that degenerate player strategies indicate a flaw
in the simulation of resource exchange. He described game dynamics as
a process of transportation or conversion (i.e., a flow defined by sources,
sinks, and transducers), and he described player exploits as "energy
spikes." In my physicist's eyes, this is just a way of saying that
game simulations usually fail to model the conservation of energy correctly
(as an example, multi-body simulations used in astrophysics
perform error correction based on energy checksums). Degenerate player
strategies as LeBlanc describes them are simply perpetual
devices discovered by the player -- or at least a vast heat reservoir
to tap into.
In
other words, the solution to many such problems might be found in modeling
the economy of transactions accurately. This is a hot topic for massively
multiplayer games; this year's GDC offered Zach Simpson's lecture
on In-Game Economics in Ultima
Online. LeBlanc himself settled for a different solution, namely
dampening the system dynamics to prevent spikes. From a physicist's
experience, adding friction can only slow down every process,
without addressing the real problem. His advice that designers should
understand and tune exchange rates is certainly to the point, as is
his recommendation to prototype early and test often games that exhibit
emergent behavior. He also pointed out that introducing feedback loops
into the system can have undesirable consequences: positive
feedback (combined with an infinite energy supply, I would add) creates
extremely unstable situations, while strong negative feedback can make
the system too stable. Friction that overwhelms every other force will
bring any system to a grinding halt.
All
in all, the discussion of game dynamics in terms of nonlinear dynamics
certainly opens an intriguing area of discussion, but I would
advise game designers to proceed cautiously. The majority of popular
science publications on nonlinear dynamics use the jargon without comprehending
the underlying concept, and even physicists have applied them in sloppy
and reckless ways. Beyond metaphor, there might be little practical
use for this.
LeBlanc
concluded his presentation by reviewing ways that various flavors of
"fun" might emerge from toying around with a complex
system, and the dreaded issue of "narrative" came up again.
His claim that complexity gives you the proverbial "infinite number
of monkeys" does not convince me, mathematically nor as
a professional storyteller. Marc LeBlanc proposes "embedded (authored)
narrative" as a complement, and wants game designers to restrict themselves
to the major story arcs. While I consider "emergent narrative" a meaningless
concept, abdication of authorship alone will not suffice.
This
uneasy marriage of simulation-driven and scripted events fell apart
when Marc LeBlanc made a case for "limited non-interactive
moments." Certainly letter-boxing in-game cinematics and cut scenes
is a visual cue to the player that he has entered a "hands off"
sequence, but this technique does not remove the tension
between the designer's desire for authorship and the player's desire
for control. Game play is never "largely" emergent -- good
narrative inevitably has long-range correlations and convergence points
that impose constraints on the results of interactivity. I
visibly annoyed one game designer by pointing out that interaction that
is irrelevant to the chain of events at large is shallow and meaningless.
Many game designers are painfully aware of this, and the workaround
commonly used is a "Paris and the Golden Apple" hack -- at
the end of the game, the player gets to choose one of two or three possible
outcomes. (Incidentally, this kind of choice does not have
in-game consequences.) A good example is System Shock 2, and
some might be generous enough to include the cheesy ending
of Half-Life as well.
An
example mentioned during the discussion put the conflicting forces between
authorship, emergence and exploitable features in a "mini narrative" nutshell: in System Shock, the
last bullet in a clip did double damage. It is easy to see how such
a simulation patch could be turned on its head once the player became
aware of it.
LeBlanc
offered valuable practical advice based on his experiences at Looking
Glass: simplify game elements but use them in conjunction with each
other, focus on interaction instead of element complexity, and settle
for a two-tiered system architecture with a few solid foundation systems
that are expected to survive the development process unchanged. It is
as difficult for the game designer to predict the outcome of a set of
rules as it would be for the player, since complex systems easily outgrow
the human mind's ability to control and adjust. The slides of Marc LeBlanc's
GDC 1999 and 2000 presentations are available as Powerpoint
files.
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Game
Design and Game Culture Panel Discussion
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