Towards a Computational Narration of Inner World

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Towards a Computational
Narration of Inner World
Zhu, Jichen
jzh@mail.ucf.edu
Department of Digital Media, University of
Central Florida
Narrative, as it evolves with technological
developments, constantly reinvents itself in
order to better capture new social orders
and individual experiences. As an emerging
cultural expression, however, most computer-
generated narrative works are still restricted
to an action-based, goal-driven aesthetics,
leaving little space for characters’ inner world.
This paper proposes to expand the range of
computer-generated narrative by addressing
this imbalance between the “physical” and
the “internal.” It presents our approach
for algorithmically narrating characters’ inner
world by leveraging the synergy between
modernist stream of consciousness literature
and contemporary research in artificial
intelligence and cognitive science. The
Riu
system, a text-based computational narrative
system inspired by Woolf’s novel
Mrs.
Dalloway
, is provided as a case study towards
this new direction.
1. Computer-Generated Narrative
Contemporary forms of narrative have evolved
rapidly as digital technologies continue to be
integrated in modern society. New conventions
at the levels of both content and discourse
have been established to reflect the constantly
changing relationship between human and
technology. For instance, popular science
fictions of the 1980s (e.g.,
The Terminator
)
embodied the prevailing cyborg discourse
and confusions of human identity within the
Cold War context (Edwards, 1996). Similarly,
hypertext fictions in the 1990s instantiated
the postmodernist mentality of its time by
turning everything – writer, reader, and society
– into fragments (Johnson-Eilola, 1997). In
this regard, the emerging form of
computer-
generated narrative
,
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that is, stories produced
by computer algorithms, may offer an important
cultural expression to portray our increasingly
technology-dependent modern life.
Compared to other forms of electronic literature
(e.g., hypertext fictions), the strict technological
requirements for computer-generated narrative
have confined its development largely to
the computer science community, particularly
artificial intelligence (AI). Over the past
decades, serious attempts have been made
to integrate narratology theory into existing
AI framework for story generation (Bringsjord
& Ferrucci, 2000; Cavazza & Pizzi, 2006;
Mateas, 2002; Meehan, 1976). Despite the
considerable progress the community has made,
the expressive power of computer-generated
narrative is still limited compared to its non-
digital antecedents. In particular, this paper
is concerned with the prominent goal-driven,
problem-solving aesthetics that dominate many
story generation systems. A salient example is
the
Tale-Spin
system (Meehan, 1976), which
generates stories in the spirit of: Joe Bear was
hungry; Joe couldn’t reach his food because of
certain obstacles; Joe resolved the issues; Joe
got his food.
It is true that recent narrative systems have
evolved in numerous aspects since then.
Nevertheless, this ultra-rational, "behaviorist"
narrative style, afforded by Meehan’s now-
widely-adopted planning-based framework, has
remained and been taken for granted by
many practitioners. As we become more aware
of digital media’s capability of constructing
subjective mental imagery and evoking users’
imagination and awareness (Harrell, 2009),
it is crucial to revisit some of these early
assumptions of computer-generated narrative
and critically understand the expressive
affordances as well as restrictions of the
computational techniques that we use.
This paper proposes to expand the spectrum
of computer-generated narratives by focusing
on the richness of characters’ inner world,
hidden behind the external world of actions.
This approach aligns with modernist writers’
concerns of depicting "hidden life at its
source" (Woolf, 1957 [1925]). Notice this
is not a strong AI attempt to model
human (semi-)consciousness. Instead, the
goal is to explore new ways of conveying
human subjectivity and life stories by
algorithmically generating
narratives
that are

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reminiscent of similar phenomena. Informed
by modernist literary techniques (particularly
Virginia Woolf’s work), cognitive science
discoveries and AI, this paper proposes a
new approach for generating inner narratives
and presents initial results from our on-going
narrative project
Riu
.
2. Synergy of the Old and New
As argued elsewhere (Zhu & Harrell,
2010 (forthcoming)), the overlooked synergy
between stream of consciousness literature,
artificial intelligence (AI), and cognitive science
provides valuable insights to generating stories
about characters’ inner world. In their
respective historical contexts, both stream of
consciousness literature and AI challenged
the domination of behaviorism by turning
internally
to the human psyche. Rejecting
the literary representation of characters as
the "external man", modernist writers such
as Virginia Woolf and James Joyce invented
techniques to depict the moment-by-moment
psychic existence and functioning of the
"internal man" (Humphrey, 1954). Similarly, AI
broke away from the behaviorism-dominated
scientific community in the 1950s and
legitimated human mental constructs, such as
knowledge and reasoning, as crucial subjects of
scientific inquiries.
The differences between AI and modernist
literature further dissolve when we take account
of recent cognitive science theory, a sister field
of AI. Stream of consciousness literature’s key
concern with pre-speech level of consciousness,
minimally mediated by rationality and language,
is echoed by new discoveries in cognitive
linguistics. Recent research (Fauconnier &
Turner, 2002) has confirmed that the vast
cognitive resources of "backstage cognition" are
called up unconsciously when we engage in any
language activity.
3. Generating Inner Narratives
Generating narratives about characters’ inner
world requires innovation at the story content,
discourse and algorithmic levels. The techniques
in stream of consciousness literature offer
invaluable insights into literary representations
of inner life, such as Woolf’s loosely structured
plot, the "caves" of characters’ past (Woolf,
1957 [1925]), and various modes of interior
monologues (Cohn, 1978).
The insights from planning-generated
stories illustrate the impact of underlying
computational techniques. Substantial changes
at the algorithmic level therefore are needed
to incorporate the new content and aesthetic
requirements. As we have argued (Zhu
& Ontañón, 2010), computational analogy,
influenced by related cognitive science studies,
is one of the promising directions towards
our goal. Its emphasis on similarities and
associations between different constructs is
particularly useful to establish connections
between external events and inner thoughts
(e.g., the action of "buying flowers" and flower-
related memories). Computational analogy may
also be used to depict "the train of thoughts"
by connecting a sequence of related events, one
after another.
4. Case Study:
Riu
Our generative narrative project Riu is an on-
going attempt to computationally generated
stories about characters’ inner world. Inspired
by Woolf’s novel
Mrs. Dalloway
(Woolf, 2002
(1925)), this project harnesses computational
analogy at different levels of story generation for
various narrative effects (Zhu & Ontañón, 2010).
Similar to our earlier conceptual-blending-
based (Fauconnier & Turner, 2002) project
Memory, Reverie Machine
(Zhu & Harrell,
2010 (forthcoming)),
Riu
is explicitly geared
towards algorithmically narrating characters’
inner world, through the depiction of characters’
unrolling thoughts and subjective variations of
such thoughts based on user interaction. An
excerpt of system output at the current stage of
development can be found in Fig 1.
Figure 1. Sample output of
Riu
(including user input)
Rather than ordering events in ways that lead
to a desired goal, as in many planning-based
systems,
Riu
adopts the computational analogy
algorithm of structural mapping (Falkenhainer,
Forbus & Gentner, 1989; Gentner, 1983) to