Intelligent Game Character Platform Producing Active Drama Experiences

1)游戏角色的动作控制构建叙事生态系统是许多电脑游戏的重要技术之一。本文介绍了一种反应性情节控制系统，该系统允许根据多个角色和用户行为之间的主动互动动态创造一个长期故事。在这个系统中，玩家的行为不仅会在角色之间产生反应，还会影响到长期的故事事件。情节控制系统存储了许多情节树（故事的组成部分），并将它们动态地连接在层次结构中，以并行或串联的方式生成各种可能的故事。该模型根据AND/OR条件将事件流组织到层次结构中，从而创建在单个事件中可能发生的许多可能性。一个故事是由许多情节组成的，这些情节以平行或串联的方式组织起来。在动作游戏中，电脑的行为缺乏多样性，人类玩家可以通过反复玩同一款游戏来了解电脑的行为。因此，人类玩家最终会厌倦这款游戏。因此，本文提出了一种模仿人类玩家行为的方法，即根据玩家的游戏数据创建玩家的个人资料。通过模仿不同玩家的行为，可以创造出更多不同的行动。在任务型学习习得语言技能的过程中，学习者在交流过程中，通过对信息的复述、澄清和确认，努力将信息传递给对方，达到相互理解，这是很重要的。因此，我们构建了一个NPC（非玩家角色）意义协商模型。当学习者与NPC进行对话时，NPC可以帮助学习者开始或通过协商意义功能来解决绊脚石。系统架构旨在支持几个重要的内部需求。任务模型提供基于leaner的任务，并初始化场景和NPC在虚拟环境中的位置。会话模型包括两个应用程序都可以使用的意义协商模型。当NPC回答学习者的问题时，两个应用程序都可以使用的语音识别器，以及可以用结构信息注释短语并参考相关语法解释的自然语言解析器。少

1) Action Control of Game CharactersConstructing a narrative ecosystem is one of the important technologies for many computer games. This paper presents a reactive episode control system that allows for dynamic creation of a long-term story in response to the active interaction between multiple characters and the user's actions. This system makes possible a story world where the user's actions not only create reactions among the characters that are currently present, but also influence the long-term story events. Episode control system stores a number of episode trees (components of the story) and dynamically connects them in a hierarchy, in parallel or in series to generate a variety of possible stories. This model organizes the flow of events into a hierarchy based on AND/OR conditions, creating many possibilities that could happen in a single episode. A single story is composed of a number of episodes organized in a hierarchy, in parallel or in series.2) Imitation Learning of Action … More Game CharacterIn action games, the computer's behavior lacks diversity and human players are able to learn how the computer behaves by playing the same game over and over again. As a result, human players eventually grow tired of the game. Therefore, this paper proposes a method of imitating the behavior of human players by creating profiles of players from their play data. By imitating what many different players do, a greater variety of actions can be created.3) Application for Second Language Learning SystemIn the process of acquiring a language skill by task-based learning, it's important for the learner to try to convey information to one another and reach mutual comprehension through restating, clarifying, and confirming information in the process of communications. Therefore, we construct a model of negotiation of meaning for NPC (Non-player Character). When the learner has a conversation with NPC, NPC may help learner get started or work through a stumbling block by the negotiation of meaning function. The system architecture is designed to support several important internal requirements. The Task Model provides a task based on the leaner and initializes the scenario and the position of NPC in the virtual environment. The Conversation Model includes the Negotiation of Meaning Model that both applications can use. When NPC answers the question from the learner, a speech recognizer that both applications can use, and a natural language parser that can annotate phrases with structural information and refer to relevant grammatical explanations. Less