DreamGarden: A Designer Assistant for Growing Games from a Single Prompt
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| Main Authors: | , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866918213822971904 |
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| author | Earle, Sam Parajuli, Samyak Banburski-Fahey, Andrzej |
| author_facet | Earle, Sam Parajuli, Samyak Banburski-Fahey, Andrzej |
| contents | Coding assistants are increasingly leveraged in game design, both generating code and making high-level plans. To what degree can these tools align with developer workflows, and what new modes of human-computer interaction can emerge from their use? We present DreamGarden, an AI system capable of assisting with the development of diverse game environments in Unreal Engine. At the core of our method is an LLM-driven planner, capable of breaking down a single, high-level prompt -- a dream, memory, or imagined scenario provided by a human user -- into a hierarchical action plan, which is then distributed across specialized submodules facilitating concrete implementation. This system is presented to the user as a garden of plans and actions, both growing independently and responding to user intervention via seed prompts, pruning, and feedback. Through a user study, we explore design implications of this system, charting courses for future work in semi-autonomous assistants and open-ended simulation design. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_01791 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | DreamGarden: A Designer Assistant for Growing Games from a Single Prompt Earle, Sam Parajuli, Samyak Banburski-Fahey, Andrzej Human-Computer Interaction Artificial Intelligence Computation and Language Coding assistants are increasingly leveraged in game design, both generating code and making high-level plans. To what degree can these tools align with developer workflows, and what new modes of human-computer interaction can emerge from their use? We present DreamGarden, an AI system capable of assisting with the development of diverse game environments in Unreal Engine. At the core of our method is an LLM-driven planner, capable of breaking down a single, high-level prompt -- a dream, memory, or imagined scenario provided by a human user -- into a hierarchical action plan, which is then distributed across specialized submodules facilitating concrete implementation. This system is presented to the user as a garden of plans and actions, both growing independently and responding to user intervention via seed prompts, pruning, and feedback. Through a user study, we explore design implications of this system, charting courses for future work in semi-autonomous assistants and open-ended simulation design. |
| title | DreamGarden: A Designer Assistant for Growing Games from a Single Prompt |
| topic | Human-Computer Interaction Artificial Intelligence Computation and Language |
| url | https://arxiv.org/abs/2410.01791 |