Story Designer: Towards a Mixed-Initiative Tool to Create Narrative
Structures
- URL: http://arxiv.org/abs/2210.09294v1
- Date: Tue, 11 Oct 2022 16:11:32 GMT
- Title: Story Designer: Towards a Mixed-Initiative Tool to Create Narrative
Structures
- Authors: Alberto Alvarez, Jose Font, Julian Togelius
- Abstract summary: This paper presents Story Designer, a mixed-initiative co-creative narrative structure tool built on top of the Evolutionary Dungeon Designer (EDD)
Story Designer uses tropes as building blocks for narrative designers to compose complete narrative structures by interconnecting them in graph structures called narrative graphs.
At the same time, we use the levels designed within EDD as constraints for the narrative structure, intertwining both level design and narrative.
- Score: 4.4447051343759965
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Narratives are a predominant part of games, and their design poses challenges
when identifying, encoding, interpreting, evaluating, and generating them. One
way to address this would be to approach narrative design in a more abstract
layer, such as narrative structures. This paper presents Story Designer, a
mixed-initiative co-creative narrative structure tool built on top of the
Evolutionary Dungeon Designer (EDD) that uses tropes, narrative conventions
found across many media types, to design these structures. Story Designer uses
tropes as building blocks for narrative designers to compose complete narrative
structures by interconnecting them in graph structures called narrative graphs.
Our mixed-initiative approach lets designers manually create their narrative
graphs and feeds an underlying evolutionary algorithm with those, creating
quality-diverse suggestions using MAP-Elites. Suggestions are visually
represented for designers to compare and evaluate and can then be incorporated
into the design for further manual editions. At the same time, we use the
levels designed within EDD as constraints for the narrative structure,
intertwining both level design and narrative. We evaluate the impact of these
constraints and the system's adaptability and expressiveness, resulting in a
potential tool to create narrative structures combining level design aspects
with narrative.
Related papers
- Agents' Room: Narrative Generation through Multi-step Collaboration [54.98886593802834]
We propose a generation framework inspired by narrative theory that decomposes narrative writing into subtasks tackled by specialized agents.
We show that Agents' Room generates stories preferred by expert evaluators over those produced by baseline systems.
arXiv Detail & Related papers (2024-10-03T15:44:42Z) - Generating Visual Stories with Grounded and Coreferent Characters [63.07511918366848]
We present the first model capable of predicting visual stories with consistently grounded and coreferent character mentions.
Our model is finetuned on a new dataset which we build on top of the widely used VIST benchmark.
We also propose new evaluation metrics to measure the richness of characters and coreference in stories.
arXiv Detail & Related papers (2024-09-20T14:56:33Z) - StoryVerse: Towards Co-authoring Dynamic Plot with LLM-based Character Simulation via Narrative Planning [8.851718319632973]
Large Language Models (LLMs) drive the behavior of virtual characters, allowing plots to emerge from interactions between characters and their environments.
We propose a novel plot creation workflow that mediates between a writer's authorial intent and the emergent behaviors from LLM-driven character simulation.
The process creates "living stories" that dynamically adapt to various game world states, resulting in narratives co-created by the author, character simulation, and player.
arXiv Detail & Related papers (2024-05-17T23:04:51Z) - StoryImager: A Unified and Efficient Framework for Coherent Story Visualization and Completion [78.1014542102578]
Story visualization aims to generate realistic and coherent images based on a storyline.
Current models adopt a frame-by-frame architecture by transforming the pre-trained text-to-image model into an auto-regressive manner.
We propose a bidirectional, unified, and efficient framework, namely StoryImager.
arXiv Detail & Related papers (2024-04-09T03:22:36Z) - GENEVA: GENErating and Visualizing branching narratives using LLMs [15.43734266732214]
textbfGENEVA, a prototype tool, generates a rich narrative graph with branching and reconverging storylines.
textbfGENEVA has the potential to assist in game development, simulations, and other applications with game-like properties.
arXiv Detail & Related papers (2023-11-15T18:55:45Z) - Visual Storytelling with Question-Answer Plans [70.89011289754863]
We present a novel framework which integrates visual representations with pretrained language models and planning.
Our model translates the image sequence into a visual prefix, a sequence of continuous embeddings which language models can interpret.
It also leverages a sequence of question-answer pairs as a blueprint plan for selecting salient visual concepts and determining how they should be assembled into a narrative.
arXiv Detail & Related papers (2023-10-08T21:45:34Z) - PlotMap: Automated Layout Design for Building Game Worlds [4.74497343690049]
We introduce an extra layer of plot facility layout design that is independent of the underlying map generation method in a world-building pipeline.
We present two methods for solving these tasks automatically: an evolutionary computation based approach throughCMA-ES, and a Reinforcement Learning (RL) based approach.
We develop a method of generating datasets of facility layout tasks, create a gym-like environment for experimenting with and evaluating different methods, and further analyze the two methods with comprehensive experiments.
arXiv Detail & Related papers (2023-09-26T20:13:10Z) - TropeTwist: Trope-based Narrative Structure Generation [0.0]
We present TropeTwist, a trope-based system that can describe narrative structures in games in a more abstract and generic level.
To demonstrate the system, we represent the narrative structure of three different games.
We use MAP-Elites to generate and evaluate novel quality-diverse narrative graphs encoded as graph grammars.
arXiv Detail & Related papers (2022-03-31T16:02:17Z) - PlotThread: Creating Expressive Storyline Visualizations using
Reinforcement Learning [27.129882090324422]
We propose a reinforcement learning framework to train an AI agent that assists users in exploring the design space efficiently and generating well-optimized storylines.
Based on the framework, we introduce PlotThread, an authoring tool that integrates a set of flexible interactions to support easy customization of storyline visualizations.
arXiv Detail & Related papers (2020-09-01T06:01:54Z) - PlotMachines: Outline-Conditioned Generation with Dynamic Plot State
Tracking [128.76063992147016]
We present PlotMachines, a neural narrative model that learns to transform an outline into a coherent story by tracking the dynamic plot states.
In addition, we enrich PlotMachines with high-level discourse structure so that the model can learn different writing styles corresponding to different parts of the narrative.
arXiv Detail & Related papers (2020-04-30T17:16:31Z) - Hide-and-Tell: Learning to Bridge Photo Streams for Visual Storytelling [86.42719129731907]
We propose to explicitly learn to imagine a storyline that bridges the visual gap.
We train the network to produce a full plausible story even with missing photo(s)
In experiments, we show that our scheme of hide-and-tell, and the network design are indeed effective at storytelling.
arXiv Detail & Related papers (2020-02-03T14:22:18Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.