Planning for Individualized Experiences with Quest-Centric Game
Adaptation
Boyang Li and Mark O. Riedl
School of Interactive Computing
Georgia Institute of Technology, Atlanta, GA, USA
boyangli@gatech.edu, riedl@gatech.edu
Abstract
Planning has been extensively used to build competent
opponents in games for human players. In this paper, we
focus not on winning strategies but on creating an enjoyable
overall gaming experience by adapting human-authored
game narratives and customizing them to the players’
motivation, tastes and needs. We discuss the benefits of
modeling game narratives as plans and analyze causal
structures to build novel computational models of narrative
coherence. A planning approach to the narrative adaptation
problem is presented. The planner takes a complete
storyline comprised of several quests and iteratively
searches for modifications, deleting and inserting quests and
events, until it meets the user’s preferences. A user study
strongly suggested the proposed notion of narrative
coherence has positive influences on story aesthetics.
Introduction
Much research efforts on planning in games have been
devoted to creating competent opponents that win as much
as possible for human players. Various planning techniques
have been applied in the context of real-time and turn-
based strategy games (Chung, Buro, and Schaeffer 2005;
Sánchez-Ruiz et al. 2007; Balla and Fern 2009), first-
person shooters (Orkin 200), and contract bridge (Smith,
Nau, and Throop 1998), to name just a few. These works
focused on planning strategies for an AI player, and have
achieved success to some extent.
However, relatively few works have focused on
optimizing gaming experience of players. As pointed out
by Roberts, Riedl and Isbell (2009), the player’s overall
experience may be more important than the expected
payoff. For instance, a hard-fought battle that is lost may
be more fulfilling than an easy victory. One aspect of the
overall experience of the player is the perception of
narrative arc, which can be dynamically generated or
adapted with planning techniques.
Indeed, the narrative arc is a crucial aspect of most
modern computer games. Game designers use a storyline
to lead players through dramatically engaging sequences of
events. Role-playing games and other types of
contemporary video games usually consist of a series of
challenges, or quests, that a player is asked to complete.
Rollings and Adams (2003) define gameplay as “one or
more causally linked series of challenges in a simulated
environment.” To overcome these challenges, players have
to perform required gaming activities, such as combat or
puzzle-solving, in a virtual world. The story elements
provide motivation, set contexts for gaming activities, and
propel the game narrative forward. In short, game
storylines are used to plan for player experience.
We suggest that optimization of player’s experience
consists of presenting the right story to the right person at
the right time. The significance of this claim is twofold.
Firstly, game players usually possess diverse motivation,
tastes, and needs (Crawford 1984; Yee 2006). A one-size-
fits-all script might not be ideal. Secondly, the preferences
of players can change over time. After playing one story,
they may demand a new one. Therefore, the ability to
generate different stories may enhance replayability and
improve player experience. Finally, by addressing the first
two implications, we are working toward the potential of
games that continuously grow and change with the player
over a long period of time.
As the cost of labor to write individualized storylines can
be prohibitively expensive, AI technologies, specifically
planning, can be used to plan for player experience by
dynamically generating or adapting storylines in games. In
this paper, we concern ourselves with the problem of
customizing game narratives for role-playing games while
simultaneously maintaining the quality of the aggregated
storyline. We acknowledge that computer systems are not
capable of the same levels of creativity as humans.
Consequently, we aim to automatically adapt human-
authored game narratives, thereby leveraging human
authoring skills and creativity while at the same time
scaling up the ability to deliver unique, customized game
experience to individual players.
In this paper, we justify our stance of representing game
narratives as plans, and discuss the notion of narrative
coherence as heuristic features of the plan structure. We
then present a technique to adapt and customize human-
authored game narratives consisting of game quests. A
refinement search algorithm is used to iteratively modify a
pre-existing storyline plan until it more closely matches the
motivation, tastes, and needs of the target user. Our system
is capable of (1) generating a large variety of quest
combinations to suit the need of each individual player and
enhance re-playability (2) maintaining story quality by
maintaining narrative coherence in addition to soundness
and (3) balancing the preservation of the original stories
and the adaptation to leverage human creativity. The
storyline is adapted by adding, deleting or replacing quests.
In addition, quests themselves can be altered in content and
structure to fit the aggregated storyline.
The remainder of the paper is organized as follows: We
discuss the theoretical aspects about narratives, the
adaptation problem and the notion of narrative coherence
in the next section. After that, we deal with the practical
side of narrative adaptation and present the planning
algorithm and a detailed example. The fifth section
analyzes the theoretical authorial leverage our system
empowers game designers with. The last section concludes
this paper.
Planning and Narrative
We focus on the narrative aspect of experience, a sequence
of events with continuant subject and that constitutes a
whole (Prince 1987). In the case of our work, the narrative
is a description of the expected sequence of events that will
occur in a virtual environment. Following others (c.f.,
Young 1999; Riedl and Young 2004; Riedl 2009), we
computationally represent narratives as a plan. The plan
representation provides a formal framework to explicitly
represent causal relationships between events and reason
about them on first principles (for example, we can ask if a
narrative is sound). Further, plans closely resemble
cognitive models of narrative. Graesser et al. (1991) and
Trabasso and van den Broek (1985) in particular highlight
the importance of causalities in stories.
Cognitive science and neuroscience suggests that
planning may be a very appropriate computational means
for narratives. Young and Saver (2001) note that
dorsolateral prefrontal injuries simultaneously impair
behavioral planning and the ability to produce “narrative
account of their experience, wishes and actions” while
many other cognitive abilities remain intact. This
coincidence seems to hint on the functional similarity of
planning and narrative generation in the human brain.
Rattermann et al. (2001) suggested adult human performs
planning in an analogous manner to partial-order planning.
In summary, planning, especially partial-order planning,
seems to bear some resemblance to narrative processing
and generation mechanisms utilized by human beings.
Given the above evidence, we represent narrative as
partially ordered plans. A partial-order plan consists of
actions and temporal and causal relations. Actions encode
preconditions – conditions that must be true for the action
to be executable – and effects – conditions that become
true once the action completes. Causal links, denoted
a
1
c
a
2
, indicate that the effects of action a
1
establish a
condition c in the world necessary for action a
2
to execute.
Temporal links indicate ordering constraints between
actions.
We use additional representational structure provided by
decompositional partial order planning (DPOP) (Young
and Pollack 1994). In DPOP, abstract actions are
decomposed into more primitive actions using
decomposition recipes. Figure 1 is an example of nested
decomposition recipes. Rounded rectangles are abstract
actions and ordinary rectangles are primitive actions.
Encapsulation represents decomposition recipes and
arrows represent causal links. For clarity, no temporal links
are shown. Primitive actions outside the decompositions
are not part of the definition of the decomposition recipe,
but are necessary for causal soundness.
The Narrative Adaptation Problem
The conventional planning problem is to find a sound
sequence of actions that transforms the world from an
initial state into one that satisfies a goal situation. The
soundness guarantees correct execution in the absence of
uncertainty. The narrative generation problem, in
comparison, can be defined as finding a sound and
coherent sequence of events that narrates the
transformation of the world, which involves events, or
sequences of events, of significant interest to the audience.
Narrative generation contrasts with conventional planning
in that the entire experience replaces the final outcome as
the primary concern. For example, a tragedy or thriller
relies more on relationships between actions in the
narrative plan and less on its outcome.
This paper deals with a problem that is slightly different:
the adaptation of narratives. Instead of generating a
narrative from scratch, adaptation starts with a sound and
coherent narrative and modifies it to meet the user’s
requirements. In this paper, we start with a human-
authored game narrative. Our algorithm preserves as much
as the original narrative as possible to minimize the chance
any handcrafted aesthetic or intuitive elements are broken
because the algorithm is incapable of understanding them.
Quest-centric game adaptation applied narrative
adaptation to computer games in which the main storyline
is comprised of one or more challenges. Quests capture the
Figure 1 An Example Quest
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lete actions
desired as par
t
t
ions can ca
u
d
by addition
o
e
Adaptation
p
tation
e, we argue th
a
u
stomized to t
h
I
n doing so,
w
f
inite number
o
r
eatly improv
e
h
itecture of o
u
takes a ma
i
d
a set of play
e
be provided
b
a player mod
e
y
specify th
e
d
s DPOP. In t
h
satisfies op
e
a
nd decompos
e
s
tructed. To f
i
e
s is made.
B
a
nning provid
e
e
d to primiti
v
with effects
o
and the caus
a
y
action is on
s
tate.
f
ficient to sol
v
e
d above. Whi
l
m
, we empow
e
e
p (1) and ext
r
a
uthorial inte
n
g
oals satisfyi
n
d
ingly.
add actions a
n
h
m must be ab
l
n
ts that are
n
n
er to fail.
t
ional planni
n
o
nditions are
o
e
initial stat
e
o
ns’ effects a
r
n
d recognizab
l
because th
e
t
of the player
u
se dead en
d
o
f other actio
n
Pipeline
a
t
h
e
w
e
o
f
e
d
u
r
i
n
e
r
b
y
e
l.
e
ir
h
e
e
n
e
s
i
x
B
y
e
s
v
e
o
f
a
l
a
v
e
l
e
er
r
a
nt
.
n
g
n
d
l
e
n
o
n
g
o
n
e
.
r
e
l
e
e
y
’s
d
s.
n
s,
can r
effort
coher
e
Cu
s
modi
f
to the
quest
condi
t
goal
s
repair
satisf
y
effect
causi
n
p
lann
i
p
repr
o
De
l
p
rimi
t
simpl
y
order
i
then
a
delet
e
deco
m
deco
m
and d
deco
m
The a
d
evide
n
model
1. Te
r
p
lan i
s
2. Pla
n
flaw t
y
O
C
d
A
d
a
n
r
e
D
f
o
S
3. Re
c
esult in supe
r
must be perf
o
e
nce.
s
tomization o
f
f
ication of the
g
set of player
r
selection. W
h
t
ion quest
co
s
tate as a ques
t
ed, the quest
y
the goal. Wh
will be rem
o
n
g it to beco
m
i
ng. The go
a
o
cessing step
e
l
etion of event
s
t
ive event tha
t
y
removed al
o
i
ng constraints
a
ll other siblin
g
e
d and the pa
r
m
posed. The
r
m
position reci
p
eleting them
a
m
posed. If the
d
aptation algori
t
n
cing why the pl
a
consisting of u
n
r
mination If the
s
complete, retu
r
n
Refinement
C
y
pe:
O
pen Preconditi
o
Reusing an a
c
Adding a ne
w
Remove the
a
C
ausal Threat:
emotion, or del
e
A
bstract Acti
o
eterministically
n
d insert actio
n
e
use existing ac
t
D
ea
d
End: non-
d
o
llowing
Satisfy Prec
o
effects to a u
n
Replace Lin
k
p
recondition
w
Remove Acti
o
Do Nothing.
I
S
uperfluous Eff
o
Link effects
o
b
y actions in
t
Do Nothing.
I
c
ursion
Figure 5 Que
r
fluous effort
s
o
rmed to iden
t
f
the game
s
g
oal state of t
h
r
equirements.
h
en a quest is
o
mplete (qu
e
t
-level goal.
A
action will
b
en a quest is
n
o
ved from th
e
m
e a dead end
a
l-state modi
f
e
xecuted befor
e
s
is handled a
s
t
cannot be f
u
o
ng with any
c
. If the event
i
g
even
t
s in th
e
r
ent abstract
r
ationale is t
h
p
e are consider
e
a
ll allows the
event to be
t
hm takes a pla
n
a
n cannot be a s
n
-instantiated a
c
plan is inconsis
t
r
n.
C
hoose a flaw fr
o
o
n: non-determi
n
c
tion with a uni
f
w
action with a
u
a
ction with the
o
non-determinist
e
ting the action
t
o
n without
choose a deco
m
n
s in the deco
m
t
ions as part of t
h
d
eterministicall
y
o
ndition: Link o
n
ifying open pre
k
: Replace a
c
w
ith a link fro
m
o
n: Remove the
I
gnore the flaw.
o
rt:
o
f earlier steps
t
he superfluous
I
gnore the flaw.
st-Centric A
d
s
. Conseque
n
t
ify and restor
s
toryline start
s
h
e original pla
n
The player ca
n
added to the
e
stX) is ad
d
A
s open preco
n
b
e added to t
h
n
o longer desir
e
e
ques
t
-level
and be remo
v
f
ication is a
e
planning.
s
follows. If th
e
u
rther decom
p
c
ausal links an
d
i
s part of dec
o
e
decompositi
o
event is mar
k
h
at actions in
e
d having so
m
abstract actio
n
deleted is ab
s
n
s
tructure, a se
t
olution, and a
d
c
tions.
t
ent, fail. Other
w
o
m the plan. Sw
i
n
istically choos
e
f
ying effect
u
nifying effect
o
pen pre-conditi
o
ically choose
p
t
hreatening the l
i
Decompositi
o
m
position from
m
position into t
h
h
e decompositi
o
y
choose to do
ne of the dead
-
condition.
c
ausal link to
a
m
the dead end a
c
action from the
to pre-conditio
n
effort
d
aptation Pla
n
n
tly, extra
e narrative
s
with the
n
according
n
specify a
story, the
d
ed to the
n
ditions are
h
e plan to
e
d, its only
goal state,
v
ed during
one-time
e
event is a
p
osed, it is
d
temporal
o
mposition,
o
n are also
k
ed as un-
the same
m
e cohesion,
n
to be re-
s
tract, it is
t
of flaws
d
omain
w
ise, if the
i
tch on
e
o
n
p
romotion,
i
n
k
.
o
n: non-
the library
h
e plan, or
o
n
one of the
-
end action
a
unifying
c
tion.
plan.
n
s fulfilled
n
nin
g