Large language models have demonstrated their capabilities in storyline
creation and human-like character role-playing. Current language model agents
mainly focus on reasonable behaviors from the level of individuals, and their
behaviors might be hard to constraint on the level of the whole storyline. In
this paper we introduce IBSEN, a director-actor coordinate agent framework that
generates drama scripts and makes the plot played by agents more controllable.
The director agent writes plot outlines that the user desires to see, instructs
the actor agents to role-play their characters, and reschedules the plot when
human players participate in the scenario to ensure the plot is progressing
towards the objective. To evaluate the framework, we create a novel drama plot
that involves several actor agents and check the interactions between them
under the instruction of the director agent. Evaluation results show that our
framework could generate complete, diverse drama scripts from only a rough
outline of plot objectives, meanwhile maintaining the characteristics of
characters in the drama. Our codes and prompts are available at
this https URL

IBSEN 是一种导演 - 演员协调代理框架，旨在生成剧本、控制角色行为，并确保情节向目标发展。它通过编写剧情大纲、指导演员代理角色扮演以及在人类玩家参与情景时重新安排情节，生成完整多样的剧本，同时保持戏剧角色的特性。

IBSEN：导演 - 演员代理协作以实现可控互动戏剧脚本生成

IBSEN: Director-Actor Agent Collaboration for Controllable and  Interactive Drama Script Generation

Storytelling is the lifeline of the entertainment industry -- movies, TV
shows, and stand-up comedies, all need stories. A good and gripping script is
the lifeline of storytelling and demands creativity and resource investment.
Good scriptwriters are rare to find and often work under severe time pressure.
Consequently, entertainment media are actively looking for automation. In this
paper, we present an AI-based script-writing workbench called KUROSAWA which
addresses the tasks of plot generation and script generation. Plot generation
aims to generate a coherent and creative plot (600-800 words) given a prompt
(15-40 words). Script generation, on the other hand, generates a scene (200-500
words) in a screenplay format from a brief description (15-40 words). Kurosawa
needs data to train. We use a 4-act structure of storytelling to annotate the
plot dataset manually. We create a dataset of 1000 manually annotated plots and
their corresponding prompts/storylines and a gold-standard dataset of 1000
scenes with four main elements -- scene headings, action lines, dialogues, and
character names -- tagged individually. We fine-tune GPT-3 with the above
datasets to generate plots and scenes. These plots and scenes are first
evaluated and then used by the scriptwriters of a large and famous media
platform ErosNow. We release the annotated datasets and the models trained on
these datasets as a working benchmark for automatic movie plot and script
generation.

我们提出了一个名为 KUROSAWA 的基于人工智能的剧本创作工作台，它主要处理情节生成和剧本生成的任务。我们使用故事的四个行为结构手动注释了 1000 个数据集，并训练了 GPT-3 模型，用于生成情节和场景，并提供给 ErosNow 媒体平台的编剧进行评估和使用。