CHS: Small: Narrative-Based Training Simulations Using Theory of Mind

CHS：小：使用心理理论进行基于叙述的训练模拟

• 批准号: 1526275
• 负责人: Stacy Marsella
• 金额: $ 49.3万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1526275&HistoricalAwards=false
• 关键词: CHS; Small; Narrative; Based; Training

This project will create a framework for simulation-based training that supports a learner's exploration and replay, and will exercise theory of mind skills, in order to deliver the full promise of social skills training. The term Theory of Mind (ToM) refers to the human capacity to use beliefs about the mental processes and states of others. In order to train social skills, there has been a rapid growth in narrative-based simulations that allow learners to role-play social interactions. However, the design of these systems often constrains the learner's ability to explore different behaviors and their consequences. Attempts to support more generative experiences face a combinatorial explosion of alternative paths through the interaction, presenting an overwhelming challenge for developers to create content for all the alternatives. Rather, training systems are often designed around exercising specific behaviors in specific situations, hampering the learning of more general skills in using ToM. This research seeks to solve this problem through three contributions: (1) a new model for conceptualizing narrative and role-play experiences that addresses generativity, (2) new methods that facilitate content creation for those generative experiences, and (3) an approach that embeds theory of mind training in the experience to allow for better learning outcomes. This research is applicable to complex social skill training across a range of situations: in schools, communities, the military, police, homeland security, and ethnic conflict. This research begins with a paradigm shift that re-conceptualizes social skills simulation as the learner rehearsing a role instead of performing a role. This shift will exploit Stanislavsky's Active Analysis (AA), a performance rehearsal technique that explicitly exercises Theory of Mind skills. Further, AA's decomposition into short rehearsal scenes can break the combinatorial explosion over long narrative arcs that exacerbates content creation for social training systems. The research will then explore using behavior fitting and machine learning techniques on crowd sourced data as way to semi-automate the development of multi-agent simulations for social training. The research will assess quantitatively and qualitatively the ability of this approach (a) to provide experiences that support exploration and foster ToM use and (b) to support acquiring crowd sourced data that can be used to craft those experiences using automatic methods. This project is unique in combining cutting edge work in modeling theory of mind, interactive environments, performance rehearsal and crowd sourcing. This multidisciplinary collaboration will enable development of a methodology for creating interactive experiences that pushes the boundaries of the current state of the art in social skill training. Reliance on crowd sourcing provides an additional benefit of being able to elicit culturally specific behavior patterns by selecting the relevant crowd, allowing for both culture-specific and cross-cultural training content.

该项目将创建一个基于模拟的培训框架，支持学习者的探索和重放，并将锻炼心理理论技能，以实现社交技能培训的全部承诺。心理理论（Theory of Mind，简称ToM）是指人类利用他人心理过程和状态的能力。为了训练社交技能，基于叙事的模拟出现了快速增长，允许学习者角色扮演社交互动。然而，这些系统的设计往往限制了学习者探索不同行为及其后果的能力。支持更多生成体验的尝试面临着通过交互的替代路径的组合爆炸，这给开发人员创造所有替代内容带来了巨大的挑战。相反，培训系统通常是围绕在特定情况下练习特定行为而设计的，这阻碍了使用ToM的更一般技能的学习。 这项研究试图通过三个贡献来解决这个问题：（1）一个新的模型，用于概念化叙事和角色扮演体验，解决生成性，（2）新的方法，促进这些生成性体验的内容创建，以及（3）一种方法，将心理理论训练嵌入到体验中，以获得更好的学习效果。这项研究适用于各种情况下的复杂社会技能培训：学校，社区，军队，警察，国土安全和种族冲突。本研究从一个范式转变开始，将社会技能模拟重新定义为学习者排练角色而不是表演角色。这种转变将利用斯坦尼斯拉夫斯基的主动分析（AA），一种明确练习心理理论技能的表演排练技巧。此外，AA分解成短排练场景可以打破长叙事弧的组合爆炸，这加剧了社交训练系统的内容创作。然后，该研究将探索在众包数据上使用行为拟合和机器学习技术，作为半自动化开发多智能体模拟用于社会培训的方法。 该研究将定量和定性地评估这种方法的能力（a）提供支持探索和促进ToM使用的经验，以及（B）支持获取可用于使用自动方法制作这些经验的众包数据。 这个项目是独一无二的，它结合了思维理论建模、互动环境、表演排练和众包方面的尖端工作。这种多学科的合作将有助于开发一种创造互动体验的方法，从而推动社交技能培训的当前最先进水平。对众包的依赖提供了一个额外的好处，即能够通过选择相关人群来引出特定文化的行为模式，从而允许特定文化和跨文化的培训内容。