SGER Collaborative Research: Persistent, Adaptive, Collaborative Synthespians

这个项目探索了用持久的、适应性的、协作的、可信的合成角色填充世界的方法的发展，这些角色被称为合成角色。这些方法是学习和计划的自适应模型的扩展，以适应大型多人在线游戏中复杂的动态环境。智力价值包括以下方面的发展和评价：1。一种行为开发语言，将发现、机器学习和行为适应直接集成到语言中，允许快速开发和部署合成程序。参与者通过观察和建模其他代理的活动来识别和发现计划的框架。这项研究的预期结果是能够创建具有许多参与者的复杂虚拟世界，支持人与机器之间的智能和有效交互。更广泛的影响：对我们如何相互作用和合作的科学理解将受益于我们模拟具有动态和不断发展的个人和群体行为的复杂环境的能力。在这个项目中，构建和建模这些环境和行为是在游戏环境中完成的。从长远来看，这项工作将影响和改变教育和娱乐领域。此外，能够模拟大型协作和互动场景也将帮助我们理解和模拟社会学家和经济学家感兴趣的大型社会动态现象。

This project explores the development of methodologies for populating worlds with persistent, adaptive, collaborative, believable synthetic actors, referred to as Synthespians. These methods are extensions of adaptive models of learning and planning to accommodate the complex, dynamic environments in massive multi-player online games. The intellectual merit includes the development and evaluation of:1. A behavior development language, with discovery, machine learning, and adaptation of behaviors directly integrated into the language, allowing for the rapid development and deployment of Synthespians.2. A framework for the actors to recognize and discover plans by observing and modeling the activities of the other agents.An expected outcome of this research is the ability to author complex virtual worlds with many participants that support intelligent and effective interaction between people and machines.Broader Impact: A scientific understanding of how we interact with each other and collaborate will benefit from our ability to simulate complex environments with dynamic and evolving individual and group behaviors. In this project, building and modeling such environments and behaviors is done within a gaming context. This work will in the long run effect and change the fields of education and entertainment. In addition, being able to model large collaborative and interactive scenarios will also help us understand and model large social dynamics phenomenon of interest to sociologists and economists.