The Ink Splotch Effect: A Case Study on ChatGPT as a Co-Creative Game
Designer
- URL: http://arxiv.org/abs/2403.02454v1
- Date: Mon, 4 Mar 2024 20:14:38 GMT
- Title: The Ink Splotch Effect: A Case Study on ChatGPT as a Co-Creative Game
Designer
- Authors: Asad Anjum, Yuting Li, Noelle Law, M Charity, and Julian Togelius
- Abstract summary: This paper studies how large language models (LLMs) can act as effective, high-level creative collaborators and muses'' for game design.
Our goal is to determine whether AI-assistance can improve, hinder, or provide an alternative quality to games when compared to the creative intents implemented by human designers.
- Score: 2.778721019132512
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: This paper studies how large language models (LLMs) can act as effective,
high-level creative collaborators and ``muses'' for game design. We model the
design of this study after the exercises artists use by looking at amorphous
ink splotches for creative inspiration. Our goal is to determine whether
AI-assistance can improve, hinder, or provide an alternative quality to games
when compared to the creative intents implemented by human designers. The
capabilities of LLMs as game designers are stress tested by placing it at the
forefront of the decision making process. Three prototype games are designed
across 3 different genres: (1) a minimalist base game, (2) a game with features
and game feel elements added by a human game designer, and (3) a game with
features and feel elements directly implemented from prompted outputs of the
LLM, ChatGPT. A user study was conducted and participants were asked to blindly
evaluate the quality and their preference of these games. We discuss both the
development process of communicating creative intent to an AI chatbot and the
synthesized open feedback of the participants. We use this data to determine
both the benefits and shortcomings of AI in a more design-centric role.
Related papers
- Game Plot Design with an LLM-powered Assistant: An Empirical Study with Game Designers [29.54980724240688]
We introduce GamePlot, an LLM-powered assistant that supports game designers in crafting immersive narratives for turn-based games.
Our user study with 14 game designers shows high levels of both satisfaction with the generated game plots and sense of ownership over the narratives.
arXiv Detail & Related papers (2024-11-05T01:26:35Z) - ChatPCG: Large Language Model-Driven Reward Design for Procedural Content Generation [3.333383360927007]
This paper proposes ChatPCG, a large language model (LLM)-driven reward design framework.
It leverages human-level insights, coupled with game expertise, to generate rewards tailored to specific game features automatically.
ChatPCG is integrated with deep reinforcement learning, demonstrating its potential for multiplayer game content generation tasks.
arXiv Detail & Related papers (2024-06-07T08:18:42Z) - I-Design: Personalized LLM Interior Designer [57.00412237555167]
I-Design is a personalized interior designer that allows users to generate and visualize their design goals through natural language communication.
I-Design starts with a team of large language model agents that engage in dialogues and logical reasoning with one another.
The final design is then constructed in 3D by retrieving and integrating assets from an existing object database.
arXiv Detail & Related papers (2024-04-03T16:17:53Z) - Instruction-Driven Game Engines on Large Language Models [59.280666591243154]
The IDGE project aims to democratize game development by enabling a large language model to follow free-form game rules.
We train the IDGE in a curriculum manner that progressively increases the model's exposure to complex scenarios.
Our initial progress lies in developing an IDGE for Poker, a universally cherished card game.
arXiv Detail & Related papers (2024-03-30T08:02:16Z) - Designing Mixed-Initiative Video Games [0.0]
Snake Story is a mixed-initiative game where players can select AI-generated texts to write a story of a snake by playing a "Snake" like game.
A controlled experiment was conducted to investigate the dynamics of player-AI interactions with and without the game component in the designed interface.
arXiv Detail & Related papers (2023-07-08T01:45:25Z) - WinoGAViL: Gamified Association Benchmark to Challenge
Vision-and-Language Models [91.92346150646007]
In this work, we introduce WinoGAViL: an online game to collect vision-and-language associations.
We use the game to collect 3.5K instances, finding that they are intuitive for humans but challenging for state-of-the-art AI models.
Our analysis as well as the feedback we collect from players indicate that the collected associations require diverse reasoning skills.
arXiv Detail & Related papers (2022-07-25T23:57:44Z) - CCPT: Automatic Gameplay Testing and Validation with
Curiosity-Conditioned Proximal Trajectories [65.35714948506032]
The Curiosity-Conditioned Proximal Trajectories (CCPT) method combines curiosity and imitation learning to train agents to explore.
We show how CCPT can explore complex environments, discover gameplay issues and design oversights in the process, and recognize and highlight them directly to game designers.
arXiv Detail & Related papers (2022-02-21T09:08:33Z) - Adversarial Random Forest Classifier for Automated Game Design [1.590611306750623]
We describe an experiment to attempt to learn a human-like fitness function for autonomous game design in an adversarial manner.
While our experimental work did not meet our expectations, we present an analysis of our system and results that we hope will be informative to future autonomous game design research.
arXiv Detail & Related papers (2021-07-26T22:30:38Z) - Learning-based pose edition for efficient and interactive design [55.41644538483948]
In computer-aided animation artists define the key poses of a character by manipulating its skeletons.
Character pose must respect many ill-defined constraints, and so the resulting realism greatly depends on the animator's skill and knowledge.
We describe an efficient tool for pose design, allowing users to intuitively manipulate a pose to create character animations.
arXiv Detail & Related papers (2021-07-01T12:15:02Z) - SuSketch: Surrogate Models of Gameplay as a Design Assistant [1.9222706856050082]
This paper introduces SuSketch, a design tool for first person shooter levels.
SuSketch provides the designer with gameplay predictions for two competing players of specific character classes.
The interface allows the designer to work side-by-side with an artificially intelligent creator.
A user study with 16 game developers indicated that the tool was easy to use, but also highlighted a need to make SuSketch more accessible and more explainable.
arXiv Detail & Related papers (2021-03-22T11:05:27Z) - Teach me to play, gamer! Imitative learning in computer games via
linguistic description of complex phenomena and decision tree [55.41644538483948]
We present a new machine learning model by imitation based on the linguistic description of complex phenomena.
The method can be a good alternative to design and implement the behaviour of intelligent agents in video game development.
arXiv Detail & Related papers (2021-01-06T21:14:10Z)
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.