Intelligent Game Character Platform Producing Active Drama Experiences

1)游戏玩家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。本文提出了一种反应式情节控制系统，允许动态创建一个长期的故事，以响应多个字符和用户的行动之间的积极互动。该系统使得故事世界成为可能，其中用户的动作不仅在当前存在的角色之间产生反应，而且还影响长期的故事事件。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一个层次结构中，并行或串行地生成各种可能的故事。该模型基于AND/OR条件将事件流组织到层次结构中，从而在单个事件中创建可能发生的许多可能性。一个故事是由许多情节组成的，这些情节以层次结构、平行或串联的方式组织起来。2）动作模仿学习 ...更多信息 在动作游戏中，计算机的行为缺乏多样性，人类玩家能够通过一遍又一遍地玩同一个游戏来学习计算机的行为。结果，人类玩家最终厌倦了游戏。因此，本文提出了一种模仿人类球员的行为，从他们的比赛数据创建球员的配置文件的方法。通过模仿许多不同的玩家所做的事情，可以创造出更多种类的动作。3）第二语言学习系统的应用在通过任务型学习获得语言技能的过程中，学习者在交流过程中通过重述、澄清和确认信息来试图向彼此传达信息并达成相互理解是很重要的。因此，我们构建了一个NPC（非玩家角色）的意义协商模型。当学习者与NPC进行会话时，NPC可以通过意义功能的协商帮助学习者开始或克服障碍。系统架构旨在支持几个重要的内部需求。任务模型根据NPC在虚拟环境中的位置和场景提供任务。对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回答来自学习者的问题时，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引用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