# Snake Story: Exploring Game Mechanics for Mixed-Initiative Co-creative
Storytelling Games

Daijin Yang<EMAIL_ADDRESS>Northeastern University360 Huntington
Ave.BostonMAUSA02115 ,  Erica Kleinman<EMAIL_ADDRESS>Northeastern University360 Huntington Ave.BostonMAUSA02115 ,  Giovanni Maria
Troiano<EMAIL_ADDRESS>Northeastern University360 Huntington
Ave.BostonMAUSA02115 ,  Elina Tochilnikova<EMAIL_ADDRESS>Northeastern University360 Huntington Ave.BostonMAUSA02115 and  Casper
Harteveld<EMAIL_ADDRESS>Northeastern University360 Huntington
Ave.BostonMAUSA02115

(2024)

###### Abstract.

Mixed-initiative co-creative storytelling games have existed for some time as
a way to merge storytelling with play. However, modern mixed-initiative co-
creative storytelling games predominantly prioritize story creation over
gameplay mechanics, which might not resonate with all players. As such, there
is untapped potential for creating mixed-initiative games with more complex
mechanics in which players can engage with both co-creation and gameplay
goals. To explore the potential of more prominent gameplay in mixed-initiative
co-creative storytelling games, we created Snake Story, a variation of the
classic Snake game featuring a human-AI co-writing element. To explore how
players interact with the mixed-initiative game, we conducted a qualitative
playtest with 11 participants. Analysis of both think-aloud and interview data
revealed that players’ strategies and experiences were affected by their
perception of Snake Story as either a collaborative tool, a traditional game,
or a combination of both. Based on these findings, we present design
considerations for future development in mixed-initiative co-creative gaming.

storytelling games, mixed-initiative co-creativity, co-creation, co-creative
storytelling, casual creators, generative AI, GPT-3

††journalyear: 2024††copyright: rightsretained††conference: Proceedings of the
19th International Conference on the Foundations of Digital Games; May 21–24,
2024; Worcester, MA, USA††booktitle: Proceedings of the 19th International
Conference on the Foundations of Digital Games (FDG 2024), May 21–24, 2024,
Worcester, MA, USA††doi: 10.1145/3649921.3649996††isbn:
979-8-4007-0955-5/24/05††ccs: Software and its engineering Interactive
games††ccs: Applied computing Computer games

##  1\. Introduction

Mixed-initiative co-creative storytelling games (Kreminski et al., 2020b)
belong to a game genre that amplifies the playfulness of story creation
through gameplay elements (Compton and Mateas, 2015). In these games, players
interact with game systems and AI in a collaborative manner to generate a
story through play (Sun et al., 2023; Kreminski et al., 2020b; Samuel et al.,
2016; Xi et al., 2021; Kreminski et al., 2022). For example, in ”Why Are We
Like This?” by Kreminski et al. (Kreminski et al., 2020b), a rule-based AI
lays the groundwork for a story world, complete with foundational characters,
relationships, and backstories before players dive into the game. The AI then
continues to present brief action ideas, which players can choose and expand
upon through their own narratives. These player decisions dynamically
influence the relationships between characters and the evolving histories of
the story world.

In many ways, these games are a form of creative writing support, facilitating
a mixed-initiative interaction (Deterding et al., 2017) where humans and AI
collaboratively craft stories. As such, they have the potential to democratize
the creative writing experience for more non-serious creators (Compton and
Mateas, 2015), who may place value on the playful and enjoyable nature of the
process, which is then amplified by the game rather than the quality of the
final written product.

That being said, the existing state of the art for mixed-initiative co-
creative storytelling games places the generation of the story as the core,
and often sole, element of the gaming experience. For example, “Why Are We
Like This”, introduced above, permits the player to select actions and
dialogue for the characters almost like a director in a play (Kreminski et
al., 2020b). From a narrative game standpoint, this is an appropriate design
approach. And from a broader perspective, it is likely the result of co-
creative storytelling and gameplay mechanics conceptually being at odds with
one another. As one can imagine, having to react to time-sensitive “twitch”
mechanics (Brathwaite and Schreiber, 2009) makes it challenging for players to
consider appropriate narrative progression or dialogue. However, simply
accepting this as a fact disregards the potential for integrating co-creative
processes within broader or more mechanically complex gaming experiences where
co-creation is not the sole objective. In addition to creating novel and
unique co-creative gaming experiences, such an approach may broaden the appeal
of mixed-initiative co-creative storytelling games to a wider audience and, as
explained above, make creativity more approachable.

To explore this possibility, we pose the following research questions: 1) How
can we blend creative collaboration with more prominent game mechanics? 2) How
do players engage with games that integrate both gameplay and co-creative
elements?

To answer the first question, we adopted a research-through-design approach
(Frayling, 1993) and designed and developed Snake Story, blending the
traditional Snake game with a GPT-3-based co-writing system. In the game,
players use the snake’s movement to select AI-generated text segments to add
to an ever-growing narrative. As the game progresses, the player must balance
the survival of the growing snake with the quality and coherence of the story,
effectively combining the storytelling element with more complex gameplay
mechanics and clear gameplay goals.

To answer the second question, we conducted a qualitative user study with 11
participants, collecting think-aloud, interview, and observation data.
Analysis of the data revealed that players experienced limited authorship in
co-creating stories within the game. Additionally, players demonstrated varied
strategies and perceptions regarding their role within the gameplay
experience, with there being a relatively clear breakdown of participants
seeing themselves as either a (1) player, (2) writer, or (3) reader as a
consequence of experiencing the gameplay offered by our game. Based on these
results, we discuss how to design future games like Snake Story to better
appeal to each role type. In all, we summarize our key contributions as
follows:

  * 1)

We present a unique GPT3-based mixed-initiative co-creative storytelling game
that mixes the goal of creating a story with more complex gameplay mechanics
and explicit gameplay goals.

  * 2)

Based on the results of a user study, we present insights into how players
experienced the game and perceived their role in relation to the storytelling
and gameplay goals and provide recommendations for the design of future games
that seek to follow the same approach as Snake Story.

##  2\. Related Work

###  2.1. Ruled-AI-Based Mixed-Initiative Co-Creative Storytelling Games

The intrinsic playfulness of casual creativity (Compton and Mateas, 2015;
Kreminski et al., 2020a) lies at the center of mixed-initiative co-creative
storytelling games. This genre leverages human curiosity for co-creation,
enhancing the writing experience with simple game mechanics. Predominantly,
rule-based AI serves as the key technological underpinning in these games.

An example is IMPROV, designed by Kybartas et al., based on GLUNET, a semantic
database containing associations between words (Kybartas and Bidarra, 2015).
In the game, players initially select a few words from the semantic database,
and then a rule-based AI generates a story’s opening and closing lines based
on these players’ selections. The player’s goal is to complete the story
through their own writing. Nevertheless, due to the lack of consistency checks
and a world model, it’s easy for players to create stories that lack
meaningful coherence.

In Samuel et al.’s Writing Buddy (Samuel et al., 2016), this issue is
partially addressed by generating a story outline for players. The game is
driven by more complicated rule-based AIs: the social simulation system
Ensemble (Samuel et al., 2015) and the play trace analyzer Playspecs (Osborn
et al., 2015). In this game, players strategically piece together a series of
brief, pre-defined narrative goals to form the framework of a story. This
narrative skeleton evolves as players make choices, ensuring that each
decision shapes the unfolding tale. Following the construction of this
outline, players can flesh out these narratives with rich, detailed prose.

Another solution to this issue is to offer players a dynamically changing
narrative world that provides specific action suggestions based on player
interactions and continuously adapts the narrative in real time. For example,
WAWLT by Kreminski et al. (Kreminski et al., 2019), as mentioned in the
introduction section, employs Felt, a rule-based AI, to create initial
settings and character dynamics. It offers action suggestions for player
expansion, dynamically reshaping character relationships and histories.
However, a playtest revealed that the action suggestions were occasionally
inappropriate, leading to players losing direction in the game. Building upon
Writing Buddy and WAWLT, Kreminski et al. (Kreminski et al., 2022) also
developed Loose Ends to counteract the aimlessness seen in the previous
systems while still upholding the sense of co-authorship for players. Loose
Ends differentiates itself by introducing more complex narrative goals that
involve sequences of events with the possibility to include specific
characters and constraints, enhancing personalization and depth in
storytelling. Furthermore, unlike Writing Buddy, which merely directs the
story toward player-set goals, Loose Ends’ AI actively proposes new goals to
maintain coherence and build upon the existing story, effectively acting as a
collaborative writing partner.

In contrast to the above approach of positioning players as primary creators,
Reed et al. developed Ice-Bound (Reed et al., 2014). In this game, players
assume the role of an assistant to an AI writer, altering the overall
narrative direction by selecting from various rule-based generative
storytelling suggestions.

Beyond AI providing suggestions based on player actions, which players then
select and write to alter a narrative, prior work has explored other forms of
mixed-initiative mechanics. For instance, in TaleBox by Castano et al.
(Castaño et al., 2016), an AI system powered by GLUNET (Kybartas and Bidarra,
2015) generates vocabulary cards that align with the game’s evolving narrative
objectives. Players strategically use these cards to craft actions that
advance toward these set goals. The AI assesses the players’ actions for
coherence, allowing only those that adhere to a predefined standard. The game
operates on a turn-based system, where players receive different vocabulary
cards each turn. Cards not utilized by the end of a turn are discarded.
Nevertheless, the lack of playtest reports makes it unclear what impact these
mechanics have on the players’ writing and gameplay experiences. Building on
the foundation of TaleBox, Perez et al. designed TaleMaker (Bueno Perez and
Bidarra, 2022), a multiplayer, card-based storytelling game. Initially, one
player sets the theme of the story. In each subsequent turn, an AI-based on
WordNet (Miller, 1995) provides players with eight vocabulary cards related to
the current story, chosen from categories selected by the players (such as
plants, food, tools, etc.). Players then use these vocabulary cards to form a
sentence. Afterward, all players vote on the constructed sentences, and the
one with the most votes is incorporated into the story. Quantitative analysis
clearly shows that the stories generated are of high quality, and the game is
generally well-received by players. However, despite acknowledging in the
discussion section that players have mixed feelings regarding the game
mechanics’ influence on creative output, the authors did not pursue a
comprehensive study to delve into the nuanced player responses to the
prominent game mechanics.

###  2.2. Language-Model-Based Mixed-Initiative Co-Creative Storytelling Games

The advent of language models (LM) ushers in a new era for mixed-initiative
co-creative storytelling games. Previously, the tendency to use rule-based AI
as the core for story generation stemmed from the inability of language models
to generate coherent writing suggestions and narratives, which could
potentially distract players (Kreminski et al., 2020b). However, recent
advancements in language models, such as GPT-2 (Radford et al., 2019) and
GPT-3 (Brown et al., 2020), have been demonstrated to produce text
indistinguishable from human-written content (Köbis and Mossink, 2021; Clark
et al., 2021). This development has opened up new possibilities for applying
LMs in mixed-initiative co-creative storytelling games. LMs transcend the
limitations of rule-based AIs that provide mere story outlines, instead
delivering rich, prose-level narrative contributions. This capability opens up
a boundless landscape of narrative possibilities, granting players the freedom
to navigate and shape an infinite storytelling universe.

For example, AI Dungeon (Latitude, 2023), a mixed-initiative co-creative
storytelling game developed by Latitude, leverages LM to create an infinitely
branching narrative, allowing players to embark on unique adventures limited
only by their imagination. In this text-based game, players can type in any
action or dialogue they can think of, and the AI dynamically generates a
response, crafting a story in real time that adapts to the player’s inputs.
The game blurs the line between player and creator, fostering an immersive
exploratory experience driven by players’ curiosity regarding the unfolding
narrative.

However, as a game, AI Dungeon falls short in offering incentives to players,
relying solely on their initiative for exploration. This approach can lead to
a swift decline in players’ engagement and enthusiasm (Xi et al., 2021). To
enhance LM-based mixed-initiative co-creative storytelling games beyond just
exploration, simple game mechanics are incorporated to maintain player
engagement and promote a state of flow. Xi et al. (Xi et al., 2021) introduced
KuiLeiXi, an AI-powered chatting game embedded within the romance simulation
mobile game Yu Jian Love (Love, 2019). In the game, players interact with a
GPT-2-based AI. Through conversation, players steer the AI towards producing
text that achieves pre-defined game goals, such as consenting to reduce the
price of an item.

Sun et al. (Sun et al., 2022, 2023) introduce more mechanics into LM-based
mixed-initiative co-creative storytelling games. In their game 1001 Nights,
players navigate storytelling and battle phases. Playing as Shahrzad, a
character in the traditional “1001 Nights” story, they guide an AI King in
creating tales tied to four distinct weapons. After making the stories, they
fight the King with these weapons. The ultimate goal is to reforge Shahrzad’s
destiny, diverging from her classic narrative.

Nevertheless, current mixed-initiative co-creative storytelling games,
including 1001 Nights, primarily emphasize co-creativity, with the co-writing
aspect often being the sole focus. In 1001 Nights, for instance, players are
assured victory in the battle phase, a feature that simplifies the gaming
experience. Such an approach does not fully explore the integration of co-
creative storytelling into more diverse gaming elements, where narrative
generation is not the only goal. There remains an opportunity for further
research on how to incorporate more intricate gameplay mechanics into mixed-
initiative co-creative storytelling games.

##  3\. Snake Story

(a) In-game scene 1. (A) “Snake” game part; (B) “Story” part; (C) timer; (D)
Generated Texts with corresponding candy indicator; (E) life point indicator.
Players can choose to eat one candy, and the corresponding text segment will
be added to the story.

(b) In-game scene 2. If the players pick up a blue candy in the last round, a
special yellow candy will appear on the map that allows players to input their
own text in (F).

(c) End-game scene. The game will end if players run out of life points, and
this end scene will appear.

Figure 1. Snake Story Scenes.

To study how mixed-initiative co-creation can work with more complex
mechanics, we created Snake Story, which combines a GPT3-based mixed-
initiative co-writing system with the Snake game. We adopted a research-
through-design approach (Frayling, 1993), focusing on generating answers
through our design efforts rather than examining solutions proposed by others.
This approach was particularly necessitated by our interest in the use of GPT
in games, an area that has not yet been extensively investigated (Gallotta et
al., 2024).

The Snake game is a classic video game concept where the player controls a
line (representing a snake) that grows in length (Sharma et al., 2019). The
primary objective is to navigate the line around the play area to pick up food
(causing the snake to grow) while avoiding collisions with the walls and the
snake’s own ever-expanding body. Each time the snake eats a piece of food,
typically depicted as a dot or apple, it grows longer, making the game
increasingly challenging as time goes on. The game continues until the snake
collides with itself or the wall. We were inspired to use this game for our
design because:

  * 1)

Gameplay that demands rapid decision-making (sometimes referred to as “twitch”
gameplay (Brathwaite and Schreiber, 2009)) is not only missing from current
mixed-initiative storytelling games but is seemingly at the opposite end of
the spectrum, as we discussed in the introduction. Hence, we started our
investigation with the game Snake, which is a classic example of this style of
gameplay, to observe the outcomes of introducing such contrasting gameplay
elements.

  * 2)

The “Snake” game is a relatively simple, classic, and well-known game, so it
does not take participants or new players a long time to learn the gameplay,
and many may already know it. Thus, it appropriately represents rapid gameplay
without introducing unnecessary complexity or a need for lengthy tutorials.

  * 3)

The snake growing over time can be seen as a metaphor for the story developing
over time. As such, the non-narrative mechanics of the game mirrored the
storytelling element.

As shown in Fig. 1(a), Snake Story consists of two main parts: the Snake game
part (A) and the Story mixed-initiative co-writing part (B). In the Snake game
part, players will navigate the snake (grey squares as its body with a
triangle as the head) on the map (white grids) to collect candies (single-
colored squares with a number) and avoid obstacles (black squares with a
cross) as well as its own body. Collecting the candies is how the player adds
text to the story, which we describe further below. The snake has a maximum of
five life points, represented by the number of grey triangles at the bottom
left of the interface (E). As with the original Snake game, the snake will
lose one life point when its head hits an obstacle or its own body. When the
snake runs out of life, the game will end.

Figure 2. Snake Story Gameplay Flow. Snake Story is round-based. At the start
of each round, candies labeled with the numbers 1 and 2, and occasionally 3
under special conditions, will appear on the map. Each candy is associated
with a unique text segment generated by GPT-3. The game will then momentarily
pause, allowing players time to read these segments. Subsequently, players
will move the snake to hit the chosen candy, thereby incorporating its
corresponding text segment into their unfolding story.

Snake Story is round-based. Each round ends with players eating one of the
candies by navigating the snake’s head to hit it. As shown in the flow chart
Fig. 2, at the beginning of each round, two candies with numbers 1 and 2 will
be generated at two random locations that are not occupied by obstacles or the
snake. In addition to adding one grey square to the snake to make it longer,
the candies will have different special effects defined by their number. As
shown in Table 1, candies with the number 1 will grant an effect from the
first three neutral and negative effects (Red, Black, White), whereas candies
with the number 2 will grant an effect from the second three positive and
neutral effects (White, Blue, Green). The candy’s color indicates its effect,
which is randomly determined at the moment of generation. Yellow candies,
associated with the number 3, can only be generated by picking up a blue candy
in the previous round. In addition to the effects displayed in Table 1,
picking up candies is how players add text to the story, which we will
describe in detail next.

In the “Story” mixed-initiative co-writing part of the game, the title A Story
of A Snake on the top right side of the screen indicates the topic of the
story. Below the title, the story-in-progress is displayed, which evolves as
the players add story content while playing. Each candy on the board is
associated with a text segment generated by the text-davinci-003 GPT-3 model.
When players select the corresponding candy by navigating the snake to it,
they add that text to the story. The mapping of text to candy is visible to
the players and can be seen on the bottom right of the screen (D).

Among all GPT-3 models, the text-davinci-003 model was the state-of-the-art
model in text completion at the time of our study in October 2022 (OpenAI,
2023). The first two text segments in the game (i.e., the first two candies
the player has to choose between as the play) are generated by the prompt
“Write a story of a snake:”, and the text segments that come after are
generated based on the story so far. The style of the text is determined by
the temperature (OpenAI, 2023), a parameter of GPT-3 that can control the
output quality of the model. Here, we manipulate this parameter to generate
different kinds of text. For text segments that will be assigned to candies
with the number 1, the temperature is set to 0.6, making the output more
focused and coherent but potentially less creative and more repetitive. For
example: “The snake stayed there for many years while the house was slowly
remodeled and restored to its former glory. As time passed by,” or “Once upon
a time, there lived a snake in the depths of the forest. She was an old and
wise creature who rarely ventured out from her” (both number 2 red candies).
The style of the text, as generated by the model, does not interact with the
coloring of the candy. For text segments that will be assigned to candies with
the number 2 (Blue, Green, or White), the temperature is set to 1.4, which
will make the output more creative and random but potentially more nonsensical
or off-topic. For example: “the trees and hearing songs brought by the breeze.
Occasionally, he even heard rumblings from land dreaders - potential
adversaries ready to” (number 1 white candy) or “Harry the snake loved to
explore. Whether it was a backyard, intense desert landscape, or lengthy
forest he enjoyed piercing through. One day though Harry” (number 1 green
candy). Furthermore, players are not informed about the temperature difference
between the two text selections.

The story is generated in real-time, with GPT taking the entire story as its
input to generate new text segments for the players. The player’s input is
directly added to the story, meaning it will also be considered part of the
input for GPT to generate new content in the next round. The generation
process takes about 2-5 seconds.

Due to the random generation of the text segments, if players want to select
certain segments that better fit their story or storytelling goals, they will
sometimes have to select candies with negative effects, potentially making the
game more difficult, as seen in Table 1. For example, a really good segment
may be attached to a black candy, which will add obstacles when selected but
ultimately provide a more desirable continuation to the story. Alternatively,
the player may need to select a green candy to guarantee their continued
success in gameplay, but this may add an undesirable addition to the story. In
essence, this turns the game into a resource management challenge, where
players must balance the nature of the story with their ongoing success in
gameplay.

To make the gameplay flow fluently, we limit the inputs from players, and the
primary interaction is to read and select from the two AI-generated text
segments to add to the story. At the beginning of each round, when the candy
is generated, and the text segments appear on the screen, the game will pause
for 25 seconds for players to read the generated texts. Under the square that
displays the current story, there is a slide bar that serves as a timer (C),
which will begin counting down after the generated text appears. Players will
then proceed with gameplay as described above. Players can only give their own
input if they pick up the special yellow candy. If the player picks up a
yellow candy, the game will pause for 45 seconds to allow players to input
their own text. The text box that facilitates this appears in the bottom right
corner (F), as seen in Fig. 1(b).

If the player runs out of life points for the snake, the game ends, and GPT-3
will give the story an ending within 80 words by connecting the story to the
prompt “, and the story of the snake ends”. As shown in Fig. 1(c), an ending
scene will appear to display the final story, the word count, and the candies
eaten. This is the only way for the game to end.

Table 1. Candy Mechanics Details. The generated candies on the map will have one of the mechanics in the table based on their number. They will also be associated with one text segment. Number 1 candies (Red, Black, White) will be associated with a more coherent text segment; number 2 candies (White, Blue, Green) will be associated with a more creative text segment; and the number 3 (Yellow) candy will allow players to input their own texts. Color | Number | Effect Type | Effect
---|---|---|---
Red | 1 | Negative |  Reduce 1 health.
Black | 1 | Negative |  Add 3 additional obstacle blocks on the map.
White | 1 | Neutral |  No effect.
White | 2 | Neutral |  No effect.
Blue | 2 | Positive |  Generate a yellow candy next round
Green | 2 | Positive |  Restore 1 health.
Yellow | 3 | Special |  Pause the game 20 seconds longer to allow players to write their own text for this candy.

##  4\. User Study

To research how different participants interact with Snake Story, 11 game
design students (referred to as P1-P11) from a university in the United States
were recruited through social media. We aimed to recruit a sample with diverse
experience with writing and AI, and this information for our participants is
presented in Table 3.

In each experimental session, the participant was given a brief tutorial on
the game mechanics and interface of Snake Story. The participant was then
asked to play the game until the snake died, which resulted in about 10-15
minutes of gameplay per participant. The participant was also required to
engage in think-aloud protocols during gameplay, where they were asked to
explain their decisions in terms of which text segments they selected and why.
After gameplay, the participants participated in a semi-structured interview,
lasting approximately 15-20 minutes, as they were asked to evaluate the story
they wrote, explain their interaction strategies, and share their interaction
experiences and role perceptions on AI and themselves. The interview questions
are listed in Table 2.

Table 2. Semi-structured interview questions. | Text Evaluation
---|---
1. | Could you please rate the overall quality of the story?
2. | What do you think about the language/logic of the story?
3. | How much control do you feel you have over this story?
| Interaction Strategies
4. | How do you decide your selections on texts and candies in Snake Story?
5. | What is your primary goal in Snake Story?
| Experiences and Role Perceptions
6. | How do you feel about the game mechanics and the story creation in Snake Story?
7. | How would you describe the role of yourself in Snake Story?
8. | How would you describe the role of AI in Snake Story?

The game captured and stored the text segments generated by GPT-3, as well as
the participants’ individual selections and the resulting stories. The screen
and the audio were recorded during the experiment. The think-aloud and
interview data were analyzed qualitatively following an open coding method
(Khandkar, 2009). One researcher familiarized themselves with the data, coded
the data, and then later grouped the codes into clusters and derived common
themes emerging from the data. We discuss the results of this process in the
next section. University IRB approved the protocol.

##  5\. Results

Figure 3. Statistics on Players’ Text and Candy Selections. In the candy
selection bar, colors correspond to the types of candies detailed in Table 1.
The purple segment indicates the count of selected texts linked to the number
2 candies within the text selection bar. The pink segment denotes the count of
selected texts associated with number 1 candies. Lastly, the gray segment
shows how often players wrote their own text.

###  5.1. Game Log Results

As shown in Fig. 3, the 11 participants played a total of 142 rounds (M =
12.91, SD = 4.50) in Snake Story. In the Story part, the text segments that
were generated with a lower temperature (number 2 candies) (0.6) were selected
43 times (M = 3.91, SD = 1.98), while the higher temperature (number 1
candies) (1.4) texts were selected 89 times (M = 8.09, SD = 4.72).
Participants chose to write their own words (yellow candies) 10 times (M =
0.91, SD = 1.83). The 11 stories had 272.64 words on average (SD = 64.22).

In the Snake game part, 91 white candies were generated, 42 of which were
selected (46.15%); 50 black candies were generated, 18 of which were selected
(36.00%); 47 red candies were generated, 11 of which were selected (23.40%);
46 green candies were generated, 31 of which were selected (67.39%); 47 blue
candies were generated, 30 of which were selected (63.83%); 40 yellow candies
were generated, 10 of which were selected (25.00%). Three participants chose
the yellow candy (associated with the human-authored story) in the game. P3
took one without contributing any content. P6 selected six, and P11 chose
three yellow candies.

###  5.2. Qualitative Results

####  5.2.1. Self Evaluation of the Co-writing

In the Snake Story study, participants generally viewed the co-authored
narratives as linguistically proficient but lacking in logical consistency and
coherence. While the language used by the AI was appreciated for its
grammatical correctness and choice of words, participants noted a disconnect
in the narrative flow. Participant 6 articulated this by stating, “I felt the
words the AI used were really nice, and there were hardly any grammar
mistakes. But because I picked a lot of good candies (with less coherent
texts), I don’t feel like the story flows that well. ” Furthermore, all
participants perceived their authorial contribution to the co-written stories
as neutral or minimal due to the mechanics in the “Snake” game part. For
instance, P7 explained “Since the game’s mechanics kind of keeps me from the
text I want, I feel like I don’t really have much control over the story.”

####  5.2.2. Play and Creation Strategies

The mechanics in the Snake game part influenced how participants decided to
treat the generated text segments. Two out of eleven participants reported
that they never read the generated text. For instance, P3 mentioned that
“Given that it’s a game, I’m not particularly concerned about what the AI
writes. My main focus is on the gameplay itself.” Five participants opted to
give the generated texts a quick scan due to the limited pause time. To
illustrate, P8 mentioned “So basically, I just skim through the text real
quick cause I also need to focus on figuring out how to get my snake to chow
down on what I picked out for it at the same time.” On the other hand, some
participants were more interested in reading the texts more thoroughly, and
their gameplay strategies adapted to accommodate this. For example, during the
5th round, P11 commented, “I think I can find a safe path for my snake to stay
in, and then I can have extra time for reading the texts. Oh, this works!”.

Additionally, players’ storytelling choices were influenced by their game
state. In the rare case where two neutral white candies with no special
effects appeared together (see Table 1), all participants were observed to
choose the text they preferred. For instance, P11 said “The second option does
not make so much sense to me. I am going to choose the first.” The more common
case was that two different candies were generated, and the preferred text
piece was assigned to the candy with a worse effect. If the participants felt
they were in a good game state (i.e., had a lot of health and not too many
obstacles to navigate), they tended to ignore the candy effects and choose the
text they preferred. For instance, in round 2 of the game, P8 stated “That’s
(option 2) sounds too conceptual. I’m going for one even though it will reduce
my health.” A rarer case was when the preferred text piece appeared attached
to the candy, which had a positive effect; in this case, participants picked
that candy without hesitation. P10 explained “I like this Harry (the snake).
It can also restore my health. I will go with the Harry story.”

However, in most cases, participants would sacrifice their stories for easier
gameplay. The green and blue candies (candies with positive effects) were
particularly attractive to participants. To illustrate, P2 mentioned “I would
more likely go for the green candy to regain my lost HP and keep myself alive
in the game for a bit longer.”. By contrast, participants rarely chose black
and red candies (candies with negative effects). For example, P7 mentioned
that “Even though the texts in the black candy are better, I’m not really keen
on making the game more challenging. Plus, the white candy’s text is good
enough for me.” The priority to game mechanics became even stronger when the
participant was about to die. For instance, P11 explained “I really want to
choose (option) 1, but I die if I choose 1. This is a very hard dilemma. I
wish I could choose 1.”

Table 3. The Individual Reports of 11 Players. AI experiences: N (No), Y (Yes); Writing experiences: R (rich), P (Poor), N (NO); Reading Strategies: S (Skim), T (Read Thoroughly), N (Never Read); Play Strategies: I (Ignore Writing), T (Make trade-offs); Role Perception: W (Writer), P (Player), R (Reader). Player Codes | P1 | P2 | P3 | P4 | P5 | P6 | P7 | P8 | P9 | P10 | P11
---|---|---|---|---|---|---|---|---|---|---|---
AI experiences | N | Y | Y | N | N | Y | N | Y | N | Y | N
Writing experiences | R | P | N | R | R | P | N | R | N | N | N
Reading Strategies | S | T | N | N | S | S | S | S | T | T | T
Playing Strategies | T | T | I | I | T | T | T | T | T | T | T
Role Perception | W | R | P | P | R | W | R | W | R | R | R

####  5.2.3. Role Perception and Player Experiences

Analysis of our results revealed that the players perceived themselves to
align with one of three different roles, which influenced how they perceived
the game and felt about the experience.

Role 1: Writers
Three (P1, P6, P8) of the 11 participants emphasized, through their responses,
that they were focused on the generation of the story. Based on this, we
categorize these participants as “writers” who saw the game as a tool for
writing a story. All of them found the gameplay unfavorable and considered the
mechanics bothersome as they consistently interfered with their text options.
For example, the time limit made the writing stressful, as illustrated by P8,
who said “It is not that fun to create stories with this (system). I do not
have enough time to read and make decisions. That’s kind of stressful.”.
Additionally, the candy mechanics confused these players. For example, P6
mentioned “I feel like there are too many things I need to pay attention to in
the game, and the texts I want to choose often appear on candies with negative
mechanisms. It is very hard for me to create my own story.”. Moreover, the
death of the snake would often frustrate them, as illustrated by P6, who
mentioned “I’m not a fan of this game because I’m looking for a longer and
more engaging story. Right now, it just seems way too easy to get killed in
it.”

Role 2: Players
Two participants (P3, P4) emphasized a focus on playing the game and surviving
for as long as possible, ignoring the storytelling aspect. As such, we
categorize these participants as “players”. These participants liked the
gameplay but felt the collaborative aspect superfluous. P4 explained this best
by saying “My attention gets captured by the game mechanics, and I’m more
inclined to play the game rather than seriously consider the logic of the
story. I’m interested in testing the rules of the game with the aim of
winning, not crafting an interesting story. After all, playing a game and
creating are two different things.”

Role 3: Readers
The remaining six participants perceived “Snake Story” as a blended experience
with both gameplay and co-creation, where the gameplay was how they could
continue to experience the story. We categorize these participants as
“readers” due to their emphasis on being someone who experiences the story
through continued gameplay but with a notable lack of emphasis on being the
creator of the story or responsible for guiding. In other words, they were
“reading” the story, and their desire to continue reading became their
motivation to play. To illustrate this, P2 said “I keep picking the good
candies to extend the snake’s life since I’m eager to read more of the story.
… Yeah, I really think looking forward to the next part of the story could be
one of the reasons people enjoy playing this game.”

These participants also seemed to enjoy the challenges in the Snake game part.
The challenges served as motivators for participants to interact with the
system and read the generated texts. As an example, P9 illustrated “The game
itself gives me a sense of urgency, and I find that this urgency is what makes
it fun. It keeps me more engaged with the stories generated by the AI. Without
that feeling of urgency, I would spend too much time trying to come up with
stories, which would actually feel like a burden to me and take away from the
enjoyment of reading.”

##  6\. Discussion

In this section, we discuss how the three roles our participants fell within
(i.e., writers, players, and readers) may have been impacted by the game
design. Furthermore, based on our results, we can see that each of the three
roles approached the game with different objectives. Thus, different
considerations need to be made to appeal to each role. As such, we discuss how
we could possibly design games like Snake Story from the perspective of each
role.

###  6.1. Designing for Writers

The first role we saw, writers, encompassed players with strong writing
objectives and expected the gameplay to align with and support their writing
goals. Writers had high demands on content quality and often expressed
frustration when playing the game. This frustration was born from the fact
that the gameplay goals and mechanics were often at odds with their creative
aspirations and writing objectives. More specifically, writers exhibited a
preference for higher-quality text segments, but the game did not always
provide such segments or did not provide them in such a way that the player
could afford to select them. For example, the player may have needed to select
a lower quality segment to continue to live if they were on their last life.
This conflict between gameplay goals and writing goals served as the main
source of the writers’ frustration.

The writers’ experience highlights an inherent conflict between creation and
gameplay tension. Video games are designed to maintain player engagement by
offering progressively challenging tasks that match the player’s growing skill
set (Csikszentmihalyi, 2000; Baumann et al., 2016), creating a dynamic of
tension and release integral to game design (Schell, 2008). However, this kind
of tension does not align well with creative endeavors. In the realm of
creation, tension tends to shift the emphasis towards quantity rather than
quality (Biskjaer et al., 2019), which conflicts with the primary objectives
of writers focused on crafting high-quality content.

Based on these conclusions, if we are to design games like Snake Story for
writers, the gameplay systems should facilitate writing objectives rather than
being at odds with them. For instance, in Snake Story, we could assign better
text segments to the candy with positive effects. The design could further
emphasize the mixed-initiative co-writing system, offering appropriate AI
interactions for writers. This includes editing and enhancing texts composed
by humans (Shi et al., 2022; Zhao, ), filling in the narrative gaps within the
skeletal frameworks of stories (Ammanabrolu et al., 2020; Laclaustra et al.,
2014), generating ideas for narrative development (Roemmele and Gordon, 2015;
Chung et al., 2022), or guiding the direction of plots by generating coherent
subsequent sentences or paragraphs (Yang et al., 2022; Swanson and Gordon,
2012). Ideally, the game system should act as a gamified extension of the
writing process, functioning as an external motivator for writers to engage
with the system (Wiethof et al., 2021). Game objectives should be harmonized
with writing goals to avoid conflicts, and gameplay tensions should be
minimized to enhance the writing experience.

###  6.2. Designing for Players

The second role we recognized, players, encompassed participants who had no
writing goals and were engaged with only the Snake gameplay in Snake Story. On
the one hand, these players were easily engaged with the gameplay part of the
game and, overall, enjoyed their experience playing. On the other hand, the
absence of external writing goals means that these players were largely
unmotivated to engage with the story generation system during gameplay.

Overall, players demonstrate a limited interest in narratives and
collaborative creation and are probably the audience that games like Snake
Story are least suited for. While this may not be the target audience for
games like this, we can still think about design adjustments that may better
capture their interest. One option would be to enhance the mechanism
connection between gameplay and narrative. For instance, incentivizing players
through rewards for their narrative creations might be effective. This could
involve offering gameplay advantages, like additional lives, in recognition of
narrative successes, whether it be for coherence, length, rhythm, the
development of a narrative arc, or adherence to genre norms. Such a strategy
motivates players to focus on and value the narrative as a means to advance
their gameplay experience. Another option would be to try to use the design
strategies described above or in the next section to try to guide or shift
players towards a different role by better tempering or setting up their
expectations (Carstensdottir et al., 2021) for the game and perhaps
influencing them to take on goals better aligned with the reader or writer
role. Additional options may include acknowledging that players simply are not
interested in narrative creation and that the best way to engage them with the
game is not to force them to engage with the narrative. In other words, it is
essential to provide players with the option to completely separate gameplay
from collaborative creation, allowing them to independently enjoy the game
without worrying about generating a story.

###  6.3. Designing for Readers

The final role we observed, readers, encompassed players who were engaged with
the narrative creation portion of the game but not from the standpoint of
having strong writing goals. Instead, they wished to create longer stories to
continue reading what happened next. Readers were motivated to continue
playing the game as doing so was what allowed them to continue enjoying the
story of the snake. Unlike writers, readers did not feel explicit frustration
as their creative objectives did not conflict with their gameplay objectives,
as surviving longer in Snake Story means the AI generates longer stories. This
connection between gameplay and creation transformed the Snake gameplay into a
driving force for the players’ reading and helped them engage with both the
gameplay and story creation elements of the game at the same time.

While it is difficult to conclude from our results alone, it may further be
that readers felt a sense of alleviated responsibility in creating the story,
instead viewing the AI as the active writer (Yang et al., 2022) and they
themselves as only consumers. This may have helped them enjoy the story being
created without feeling the diminished sense of authorship that those
participants aligned more with a “writer’s” role experienced. From this, we
may be able to infer that readers are the ideal audience for games like Snake
Story.

Although the readers in our study were relatively pleased with their overall
experience, we can still theorize ways to improve it further. The key to
effectively crafting mixed-initiative storytelling games tailored for readers
is to reinforce the connection between gameplay and the generation of the
narrative to foster cohesive interaction. We could do this in several ways.
However, we discuss two in particular.

First, the game mechanics should be linked to the AI-generated text to
undertake narrative functions. This can help to alleviate the traditional
disconnection between game rules and fiction (Tocci, 2008), providing more
immersive experiences for readers. For instance, if the generated plots
revolve around a protagonist acquiring new abilities, the player could also
gain new gameplay abilities, reflecting the development of the narrative in
the gameplay mechanics. Of course, such an arrangement would require
implementing constraints on AI-generated content, as AI-generated texts cannot
be anticipated without imposing limitations, and it would otherwise be
difficult to ensure that the mechanics evolve in relation to the generated
narrative. Furthermore, leveraging other generative AI tools can be
instrumental in creating real-time narrative-linked game assets. A notable
example is 1001 Nights (Sun et al., 2023), where ControlNet (Zhang et al.,
2023) and a pixelization tool (Wu et al., 2022) are employed to craft
pixelated backgrounds that are thematically consistent with the
collaboratively crafted story in battle scenes.

Another option is to dynamically adjust the pacing (Coulianos, 2009) of the
gameplay to match the progression of the generated narrative. For example, a
common narrative structure (McCabe and Peterson, 1991) includes Exposition,
Inciting Incident, Rising Action, Climax, Falling Action, Resolution, and
Denouement. Based on this structure, we can increase the difficulty of the
gameplay mechanics during the narrative’s Rising Action, reach the maximum
intensity during the Climax, and then release the tension during the Falling
Action. In doing so, we may be able to reflect the events of the story in
gameplay without necessarily having to change the game mechanics themselves.

##  7\. Limitations

Our research has identified various preferences and strategies among different
types of players in mixed-initiative co-creative storytelling games, and based
on these findings, we have proposed several design suggestions. However, our
work is not without limitations. First, we selected students majoring in game
design as our subjects. While this ensured high-quality feedback from a
smaller dataset, it did not adequately represent the experiences of a broader
range of casual players and non-players. In the future, we hope to expand our
participant pool to include these unrepresented groups. Second, We acknowledge
that in choosing Snake as the basis for our game, we have created a very
specific type of gameplay experience, one that only offers a singular goal and
a limited number of mechanics. We acknowledge that games of different genres
and levels of complexity, when incorporating co-creative storytelling
elements, would create very different experiences and that the results we saw,
specifically the roles that emerged, are the result of the experience we
created. In future work, we will experiment with our mixed-initiative
mechanics but with different game genres (e.g., shooter, platformer) to
further explore and extend the player experience with gamified mixed-
initiative storytelling. Third, although players did not report any layout and
text readability issues due to the game’s user interface (UI) design, we
acknowledge that this could be a problem, for which future work may want to
inquire further about what UI best supports the player experience while
allowing for creative storytelling to emerge organically. Finally, we
acknowledge that our sample consisted of 11 people. While this is a suitable
number for qualitative and exploratory work, similar to what is seen in
existing literature (Halabi et al., 2019), we acknowledge this is a small
sample, which means that our identified roles will need to be scrutinized with
a larger (and more diverse) sample size in future work for generalizing the
results of our exploratory inquiry.

##  8\. Conclusion

We presented Snake Story, a mixed-initiative co-creative storytelling game
that integrated prominent gameplay objectives. In Snake Story, players play
the classic Snake game while collaborating with GPT-3 to co-create a story
about a snake’s adventures. This unique gameplay experience requires players
to balance their focus between the game’s traditional objectives and their
creative narrative ambitions. In our study with 11 players, the complex
interplay between gameplay mechanics and storytelling is brought to the
forefront through the diverse roles players experienced—writers, players, and
readers. Writers, charged with crafting the narrative, frequently found it
challenging to fully engage with the gameplay aspect, while players, primarily
focused on gameplay, occasionally overlooking the narrative aspects. On the
other hand, readers experienced a more balanced interaction, appreciating both
the gameplay and the story.

The insights from Snake Story suggest a nuanced approach to future game design
in this genre. For writers, the game environment should prioritize narrative
creativity, with gameplay elements that support rather than hinder the
storytelling process. Players, in contrast, would benefit from a focus on
immersive and engaging gameplay mechanics, where the narrative can serve as a
complementary feature. For readers, an ideal design would seamlessly blend
narrative and gameplay, enhancing their overall experience. This approach,
tailored to the specific preferences of different player types, points towards
a future where mixed-initiative co-creative storytelling games can more
effectively cater to a diverse gaming audience.

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