SCENE · CHOICE · CONSEQUENCE
Detroit AI Player
@BABA88611
Let the AI go through all the options in Detroit: Become Human without knowing the consequences.
Detroit AI Player organizes the chapter selections of "Detroit: Become Human" into a structured decision tree. The AI only sees the current situation and options each time and does not know the consequences. The runner then carries the choice results and cross-chapter status to the next chapter.
Project address (can be copied to AI):https://github.com/Baba88611/detroit-ai-player
PROJECT INTRO
Project introduction
Detroit AI Player is a decision-making experiment that lets the model blindly play "Detroit: Become Human". It splits thirty-two chapters into bilingual situations and options in Chinese and English. The model cannot see the results and can only answer based on the current information; the runner is responsible for updating characters, relationships and branch status.
The running code of the project uses MIT, and the compiled plot data uses CC BY-NC 4.0. The rights to the original characters, worldview and plot still belong to the relevant rights parties of "Detroit: Become Human", and Atlas only indexes it as a non-commercial experiment.
- Suitable for:People who want to compare different models of value judgments, narrative choices, and long-term decision trajectories.
- Platform:Python CLI requires a callable language model.
- Usage:Run the decision tree by chapter, let the model choose and continue to pass the generated state to the next chapter.
- License:Code MIT; data CC BY-NC 4.0, subject to original copyright boundaries.
COMMENTS & FEEDBACK
Comments and Feedback
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SOURCE & CREDIT
Atlas is responsible for the introduction and navigation, and the use still returns to the original author.
We do not mirror project files, nor do we intercept author traffic. For installation, download, version updates and the latest instructions, please refer to the project page provided by the original author.
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