Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 1 (June 2017) 71–76___________________________________________________________________________________________________________

Changing and Transforming a Story in the Frameworkof an Automatic Narrative Generation Game
Jumpei Ono

Graduate School of Software Informatics, Iwate Prefectural University
Takizawa, Iwate, 020-0693, Japan
Takashi Ogata

Department of Software Informatics, Iwate Prefectural University
Takizawa, Iwate, 020-0693, Japan
E-mail: g236m001@s.iwate-pu.ac.jp, t-ogata@iwate-pu.ac.jp

Abstract
We propose the concept of a game system that includes an automatic story-generation function based on a table-toprole playing game (TRPG). In this idea, stories are generated or transformed based on communication between a“game master (GM),” who controls the story generation, and “players (PLs),” who change and transform thecontent of a story proposed by a GM. This paper focuses on the mechanism for changing and transforming a story
proposed by the GM. In particular, the proposed mechanism has various techniques ranging from macro-leveltechniques, which are related to the entire structure of a story, to micro-level techniques, which are related to thepartial structures of a story. For instance, when the GM is a real human, these techniques in the PLs, who arecomputer agents, can produce changed and transformed stories that were not originally conceptualized by the GM.
Keywords: Automatic narrative generation game (ANGG), Integrated narrative generation system (INGS), Tabletop role playing game, Story generation, Discourse.

which are related to the overall structure of a story, tomicro-level techniques that are related to the partial
structures of a story. We aim to design and implement
the future expansion of the system.
We refer to the game system, including theautomatic narrative generation mechanism, as an“automatic narrative generation game (ANGG).” In thissystem architecture, each GM and PL can be either acomputer agent or a human. When the GM is a realhuman, a variety of narrative techniques employed by
PLs who are computer agents enable the production ofchanged and transformed stories that the GM did not
imagine originally. When both the GM and PLs arecomputer agents, they can use the narrative generation
mechanisms in the integrated narrative generation
system (INGS) described in the following section to

1. Introduction
In this study, we propose a mechanism for a computer
game system using an automatic story generation
function based on a tabletop-top role playing game
(TRPG). Here, stories are generated and transformed via
a communication loop between a “game master (GM),”
who generates the first framework of a story andcontrols or manages the subsequent story generation
process, and “players (PLs),” who modify and transformthe story that was first generated by the GM. This paper
focuses on the problem associated with the mechanism
for changing and transforming a story proposed by the
GM. Although this mechanism is currently implemented
using a simple method, in this paper, we discuss various
techniques that range from macro-level techniques,

Copyright © 2017, the Authors. Published by Atlantis Press.
This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
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Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 1 (June 2017) 71–76___________________________________________________________________________________________________________

generate a story framework and transform the story
framework into the expanded stories. Thus, the ANGG
is regarded as a kind of narrative generation systemthrough the corporative relationships between the GM
and the PLs.
As Ogata1 presented a detailed description, Fig. 1
shows an overview of the INGS architecture. From amacro perspective, the INGS is divided into three
generation processes or mechanisms, namely a story,
discourse, and representation. Ogata1 presents a detailed
list of all of the modules in the current INGS. Generally,
the story generation mechanism generates a story
structure that contains a sequence of events. Then, thediscourse mechanism transforms the story structure
generated by the story generation mechanism into a
discourse structure that contains edited by the narrative
logic, namely the structure of a narrative to be narrated.
Further, the representation mechanism transforms thenarrative structure into a surface narration using natural
language, music, and a picture image.

proposed a mechanism for expanding a scene in theframework story generated by the GM in order to makea longer story. In this paper, we focus on the aspect of
the story generation and discourse generation techniqueswith the aim of extending narrative generation
techniques in future ANGGs. These correspond to thetechniques that are used to arrange the story-generation
mechanism and discourse generation mechanism in the
INGS, and the many parts can be used in both the
ANGG and INGS. However, important differences arethat the PLs in the ANGG generate and transform aprepared story framework through the collective andcorporative process, and narrative generation is
generally conducted considering the interaction and theGM and the PLs.
2. ANGG Overview and Story and Narrative
Generation
Fig. 2 shows an overview of the story generation
process in the ANGG. From the perspective of story or
narrative generation, the ANGG comprises two types ofgeneration mechanisms by the GM and PLs. In
particular, in the first step in the communication cycle,
the GM generates the framework of a story that is to be
incrementally extended into an extended story. Then,the PLs receive the framework story to generate apartial discourse to be inserted or added to the story.
Finally, in the PL mechanism, several PLs collectively
generate a new partial narrative. Currently, this requires
a method that inserts an event between the two events inthe framework story until the decided connection
condition is satisfied for the next event in theframework story. The framework story refers to a story
in the INGS that is generated using the story generation
mechanism. On the other hand, the transformed orchanged narrative corresponds to a discourse in the
INGS that is transformed according to the discourse
mechanism. However, in practice, the PLs can also use
techniques in the story generation mechanism. In
addition, the ANGG uses the “world setting,” whichmeans both a set of elements for stories and a set of
constraint information that is used to define the range ofpossibilities.
A variety of collective or corporative narrative
generation or transformation methods can be considered
in order to extend the ANGG. Based on the current
method, all PLs propose candidates for expansions of an
original story or discourse, and only one is selected to

OutputInput
Entire control
Story
Contents
KB
State-event
Transformati
on KB
Conceptual
Dictionaries

Story
Mechanism

Discourse
Mechanism

Expression
Mechanism

Language
Notation
Dictionaries

Music KB

Image KB

Function call

Data flow

Fig. 1. The INGS Architecture.

The GM and PLs in the ANGG respectively
correspond to the story generation mechanism and thediscourse mechanism in the INGS. From the perspectiveof the GM, a story that the GM generated is changed
and transformed by the PLs into a more interesting story.
In this case, the story is called a discourse in the INGS.
The GM also controls and manages the transformationand change process to make an expanded discourse or toindicate the need to make an alternative discourse. On
the other hand, the PLs collectively change andtransform the story under the control and managementof the GM to expand it through the communication
cycle between the GM and the PLs.
Ono and Ogata2-5 presented the architecture of an
ANGG system. Ono and Ogata2 located a mechanismthat set a story world in the ANGG, and Ono and Ogata672

Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 1 (June 2017) 71–76___________________________________________________________________________________________________________

GM

PLs

Story
sequence①

Generation

③-a

Story
sequence’

Control③-b

Story
sequence

INGS that we have presented. The main types that are
relevant to the PLs are described in section 3. The
ANGG can also refer to previous research to elaborately
design the interactive mechanisms between the GM and
the PLs as well as between the PLs. In section 4, we
introduce the related previous research.

PL

②

Story
sequence’

PL

PL

INGS
Input
Story
Contents KB
State-event
Transformat
ion KB
Conceptual
Dictionaries

Entire control

Output

3. Methods for Story Generation andTransformation

Story
Discourse Expression
Mechanism Mechanism Mechanism
Language
Notation
Dictionaries

Music KB
Function call

Image KB

In this section, we introduce various mechanisms thattransform a story into various discourse structures.

Data flow

Fig. 2. A story generation process in ANGG.

3.1. Story and Discourse in a Narrative

be given to the GM. Discourses that are made by all PLs
can also be combined into the final proposed discourse.
In addition, various types of discourses may be
proposed to the GM, and include methods that embody
or extend a part of the framework story generated by theGM, and that transform the flow of the entire story.
Further, each PL plays a character in a story world, andthe narrative generation by the PLs is executed based on
the characters’ perspectives. A function in thecommunication process among PLs determines which
PL is the main character in the story world. Thus, goalplanning story generation is one of the basic narrativegeneration methods that are used. We discuss thesenarrative generation problems faced by PLs in anotherpaper.
After the PLs first propose a discourse thattransforms and changes the framework story generated
by the GM, the GM evaluates whether to directly adopt
the proposition. If the proposed discourse (or the
fragmental extension) is adopted, the GM creates a newstory that reflects the discourse proposed by the PLs. In
contrast, if the proposed discourse or the fragmental
extension is not adopted, the GM instructs the PLs torepeat the narrative generation for the framework story
until the GM decides to adopt it. After the second
process, this cycle, which is referred to as narrativetransformation by the PLs and narrative evaluation by
the GM, continues until a complete narrative is
eventually generated. As stated above, in the ANGG,
the GM has roles that include generating the first story
framework and controlling the post-game progression.
On the other hand, the main role of the PLs is totransform and change the framework story generated by
the GM in an attempt to propose partial stories.
In the above system’s architecture, the ANGG canuse story and discourse generation techniques in theFirst, the “narrative discourse mechanism” in the INGS
architecture shown in Fig. 1 provides the mostfundamental narrative mechanism that is used forchanging and transforming a story generated by thestory generation mechanism. Fig. 3 shows an example
where a story structure is transformed into a discourse
structure; a relationship specified to discourse, “presentbackward” is added to the story structure. The structures
for both the story and the discourse have similar tree
forms. Each leaf node in a story tree corresponds to an
event described with conceptual representation, which isfurther described by a case structure that consists of one
verb concept and eight types of cases, such as “agent”
and “object.” Each internal node in the tree is equivalent
to a “relationship,” such as “cause-effect” and “serial,”
combined with the child nodes. The ANGG can use thistype of method as a narrative discourse technique tochange and transform the framework of a story that is
generated by the GM.
We began this study by modifying the theory’s
context proposed by Genette7, who is a Frenchnarratologist, and we used a computational viewpoint tocreate a technological method for the design orformalization of the narrative discourse generation$Cause-effect$Sequence $Sequence
E1 E2 E3 E4

E5$Present-backward
Discourse technique($Present-backward)

E5

E4$Cause-effect$Sequence $Present-backward
E1 E2 E3

E5

E4

Fig. 3. Transformation from story structure to discourse
structure.

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Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 1 (June 2017) 71–76___________________________________________________________________________________________________________

Table 1. Classification of TV-CF rhetorical techniques.

mechanism. This allows each of the classified
techniques applied by Genette to be used as a rule for
associating an input story structure with a transformed
output discourse structure. However, the aim ofstudying the narrative discourse mechanism is not only
to apply the narratology proposed by Genette. It is also
expanded to other narrative discourse techniques. We
designed a more comprehensive narrative discourse
system by integrating various narrative discourse types,
including the following techniques, into a systematic list.

Regular

ObjectIrregular

3.2. Defamiliarization Techniques
Zhang, Ono and Ogata8 classified the methods of therelationships between a product and the story byperforming an analysis of over 5000 televisioncommercial films to define its result as “rhetorical
techniques of introducing a product into a single event.”
The previous study classified the rhetorical techniques
into either regular rhetoric or standard rhetoric during
the of production, distribution, and utilization processesof a product. On the other hand, they defined irregularrhetoric based on “defamiliarization” (“ostranenie” inRussian) or a deviation from the regular rhetoric.
Defamiliarization rhetoric indicates techniques thattransform the whole of a part or an element included ina story into an extraordinary object that is different frompeople’s ordinary feeling to strengthen the impressionof the element itself.
Table 1 shows 12 defined types of rhetoric. A“rhetoric” refers to a technique that is used to introduce
a product in an impressive way by employing anadvertising scenario, while a “single event” refers to aunit that contains several elements such as a person,
object, location, and time, which are associated with asingle action in the flow of the story. In the table,
rhetorical techniques from R1 to R3 generate scenes ofstandard or ordinary use methods of products. On theother hand, the rhetorical techniques from R4 to R12
generate defamiliarization scenes by applying theextraordinary rhetoric. The irregular techniques partially
use the “changing constraint” method, which changes
usable concepts in the conceptual dictionaries in the
INGS (Fig. 1) to adjust the semantic range of concepts
to enable them to be set into an event.

Type of Rhetoric
R1 original method of manufacturing: the original
way that the product is manufactured.
R2 original method of purchasing: the original way
that the product is purchased.
R3 core rhetoric: the way that the product is originallyused.
R4 defamiliarization: the defamiliarized way that the
Action product is used.
R5 none use of rhetoric: no deviation, just "hold."R6 character as a narrator: rather than being involvedin the story, the character sends a message to viewers
directly.
R7 state defamiliarization of the character: changing
Person all or part of the character, or the character daily uses the
product in an impossible way.
R8 action defamiliarization of the character: thecharacter does not perform the original action, but
performs defamiliarity.
R9 state defamiliarization of the product: changing allor part of the product.
R10 state defamiliarization of related things of the
product: changing all or part of the related things of theThings product.
R11 product subjectification: instead of being usedby a character, here, it emphasizes that the productexists independently.
R12 background defamiliarization: all or part of the
background is changed into
Location something entirely decorative, which is impossible to do
daily.

specific element in the story. This is done by lacking atemporal sequence and a character’s consistency incontinuous scenes in a film. For example, in a battle
scene in a war film, the use of cutting techniques byinserting a silent scene and a scene where the temporalcontinuity is ambiguous contribute to strengthening theimpression of scenes that are independent of a story’s
semantic progression.
Kanai and Kodama9 proposed a high-levelclassification of cutting techniques that (1) emphasizes
editing itself by making a differentiation or
discontinuity in the elements among continuous shots,
which includes destroying the continuity of events, (2)emphasizes the image itself by irrationalizing or
destroying the relationships between an event and theimage, which includes repetitive filming of the same
object, and (3) emphasizes the sound itself byirrationalizing the relationships between sound and theimage, which includes lacking the relationships between
speech and the visual image.
Furthermore, considering the above large
classification, Kanai9 presented the following sixteen
types of cutting technique. In the description, “dialectic”
refers to a unified whole. On the other hand, in “cutting,”
it appears as itself, and the temporal order cannot berecognized by the user. In “metric,” the continuity timeof all shots is the same. On the contrary, the continuity

3.3. Film Rhetoric by Kanai
Story cutting techniques proposed by Kanai9 aim to cut
a story’s consistency in order to strengthen only a74

Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 1 (June 2017) 71–76___________________________________________________________________________________________________________

responses from an author; the interaction cancontinuously or historically change a literary work. In
particular, texts of narrative discourses are repeatedly
produced through a process according to parameters fora reader (or narratee) as the expectation, and using thesame parameters for an author (or narrator) as thegenerative goals. These parameters are the same as
those in the Genette-based mechanism.
The cycle continues according to the interaction
between a narrator and narratee. The narrator
mechanism has a set of rules for controlling theapplication of discourse techniques based on thegenerative parameters to transform a discourse structure.
We performed the direct transformation of a discourse
structure using techniques defined by Genette’s theory.
The narratee mechanism evaluates the results bycomparing the narratee’s expectation parameters with
the narrator’s generated parameters. In the next cycle,
the narrator applies corrections according to thenarratee’s evaluation in order to achieve reader
satisfaction. However, the process eventually reaches apoint where the narratee becomes tired or when his/her
satisfaction begins to fall. When this happens,“deviation” occurs and the narrator abandons some ofthe old generative parameters and moves to a new cycleof discourse grounded on the newly found strategy. The
narratee’s expectations change according to thereconstruction.
Fig. 4 is a detailed process flow of the narrative
discourse control based on the interaction between the
narrator and narratee mechanisms. As seen in (1), thesystem selects the corresponding techniques according
to the parameter values. In (2), the Genette-based
techniques fulfill the functions in the context of the
Jauss-based control. In (3), a higher satisfaction can beobtained when a more strongly desired parameter issatisfied. The narratee indicates one parameter with thelowest satisfaction. In (4), the narratee rewrites an
expectation parameter using two different procedures.
The first rewrites the sufficiency number and degree ofdesire. The former is increased each time the narratee
receives the sufficed discourse. Finally, (5) includes“deviation” from the expectation.

time in each shot varies according to the action’s time.
“Tonal” and “overtonal” do not initially determine thecontinuity time.








(1) Dialectic metric, (2) Dialectic rhythmic, (3)Dialectic tonal, and (4) Dialectic overtonal: (1),(2), and (3), respectively have different lengths ofshots, and (4) mixes a shot with different sounds
into a sequence of shots.
(5) Temporal sequence cutting metric, (6)Temporal sequence cutting rhythmic, (7) Temporalsequence cutting tonal, and (8) Temporal sequence
cutting overtonal: These prevent a receiver from
representing the temporal sequence of events in a
cognitive manner.
(9) Characters cutting metric, (10) Characters
cutting rhythmic, (11) Characters cutting tonal, and(12) Characters cutting overtonal: These cut thecontinuity of a character, and there are no shots
where the same character continuously appears.
(13) Temporal sequence/characters cutting metric,(14) Temporal sequence/characters rhythmic, (15)Temporal sequence/characters tonal, and (16)Temporal sequence/characters overtonal: These
prevent a receiver from representing the temporalsequence of events in a cognitive manner. In
addition, there are no shots where the samecharacter continuously appears.

4. Generation by Narrative Communication
Akimoto and Ogata10,11 presented a computational
narrative model in which literary works arecontinuously changing owing to the interaction between
an author or narrator and a reader or narrator (these arecomputer agents within the system) for a narrative
discourse control mechanism in the INGS. In the systemmodeling, Jauss’ reception theory12 is simply interpreted
as a mechanism to limit the discourse process throughthe interaction between a narrator mechanism withgenerative parameters and a narratee mechanism withexpectation parameters. In this study, we mixed thisJauss-based mechanism with the Genette-based
mechanism mentioned in section 3.1 to form a modeland system that control the deviation of a narrative
discourse mechanism based on the interaction between anarrator mechanism and a narratee mechanism within anarrative.
This system is a model of Jauss’ reception theory,
where literary works are repeatedly produced according
to a reader’s expectations and the corresponding

5. Conclusions
In this paper, after we presented an overview of the
ANGG system that we developed, we considered story
generation and discourse techniques to utilize the GM75

Journal of Robotics, Networking and Artificial Life, Vol. 4, No. 1 (June 2017) 71–76___________________________________________________________________________________________________________

Narrator mechanism
Generative
goal(1) Selection of
discourse
techniques to be
applied(2) Techniqueapplication(5) Adjustment ofgenerative parameters
according to narratee
indications

Story

Discourse

References

Narratee mechanism
Expectation

1. T. Ogata, Computational and Cognitive Approaches toNarratology from the Perspective of Narrative
Generation, in Ogata, T. & Akimoto, T. (eds),
Computational and Cognitive Approaches to Narratology(IGI Global, Pennsylvania, 2016) 1-74.
2. J. Ono and T. Ogata, Architecture of a narrative
generation system based on a TRPG model: the use of an
integrated narrative generation system for knowledge
acquisition (preliminary version), Bulletin of Netw.,
Comput., Syst., and Softw. 5(1) (2016) 40-48.
3. J. Ono and T. Ogata, A design plan of a game system
including an automatic narrative generation mechanism:
the entire structure and the world settings, J. Robotics,
Networking and Artificial Life 2(4) (2016) 243-246.
4. J. Ono and T. Ogata, Towards a narrative generation
system based on a TRPG model: the use of an integrated
narrative generation system for an application system, in
Proc. 21nd Int. Symp. on Artificial Life and Robotics(2016).
5. J. Ono and T. Ogata, Architecture of a narrative
generation system based on a TRPG model: the use of an
integrated narrative generation system, in Proc. 4th IIAE
Int. Conf. on Industrial Application Engineering 2016(2016) 138-145.
6. J. Ono and T. Ogata, Implementation of a Scene
Expansion Mechanism using an Event sequence: As a
Mechanism in an Automatic Narrative Generation Game,
Proc. 3rd Int. Conf. on Knowledge Engineering (2016).
(In printing).
7. G. Genette, Narrative discourse: An essay in method,trans. J. E. Lewin (Cornell University Press, New York,1972).
8. Y. Zhang, J. Ono and T. Ogata, Single Event andScenario Generation based on Advertising RhetoricalTechniques using the Conceptual Dictionary in Narrative
Generation System, The 4th IEEE Int. Conf. on DigitalGame and Intelligent Toy Enhanced Learning (2012)
162-164.
9. A. Kanai and K. Kodama, Film edit design: Story andirrational cutting, Cognitive Studies 17(3) (2010) 444458.
10. T. Akimoto and T. Ogata, A narratological approach fornarrative discourse: Implementation and evaluation of thesystem based on Genette and Jauss, in Proc. of the 34th
annual conf. of the Cognitive Science society (2012)
1272-1277.
11. T. Akimoto and T. Ogata, An information design ofnarratology: The use of three literary theories in anarrative generation system, Int. J. Visual Design 7(3)(2014) 31-61.
12. H. R. Jauss, Literaturgeschichte als provokation,(Suhrkamp Verlag, Frankfurt am Main, 1970).

(3) Reception
evaluation

Evaluation
results

User input: story and initial value of generative goal and expectation(4) Expectation
rewriteData flow Procedure

Fig. 4. Interaction between narrator and narratee.

and PLs used in the ANGG in the future. These
techniques are provided by the story-generation
mechanism and the discourse mechanism in the INGS.
Therefore, although there is common narrativeknowledge to be used in both the INGS and the ANGG,
an important difference between the two systems is thatnarrative generation by the ANGG is performed
considering the interaction between the GM and the PLs
and the collective method among PLs. Table 2 shows acomprehensive list of narrative techniques for the GM
and the PLs including the techniques described in thispaper.
Table 2. Classification of narrative techniques.

Macro level techniques Story-generation techniques Story grammar techniques Story-discourse transformation techniques [Section 3.1]
Medial level techniques
 Goal-planning techniques
Micro level techniques
 Event transformation techniques Rhetorical techniques [section 3.2]
 Cutting techniques [section 3.3]

In the future, we plan to extend the design of an
integrated mechanism of the ANGG to incorporate
various narrative techniques, including those proposedin this paper, interactive processing between the GM
and the PLs, and collective processing among the PLs
into a system architecture that enables changeable anddiverse narrative generation.
Acknowledgements
This work is supported by the JSPS KAKENHI Grant
Number 26330258 and the Support Center for
Advanced Telecommunications Technologies Research
Grant (2015-2017).

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