SBIR Phase I: A Novel Human Robot Interaction System Using Affective Theory-of-Mind Computing to Improve User-Responses and Efficacy of Automated Tutoring

SBIR 第一阶段：一种新型人机交互系统，利用情感心理理论计算来提高用户响应和自动辅导的效率

• 批准号: 1214817
• 负责人: Kino Coursey
• 金额: $ 15万
• 依托单位: Hanson Robokind And Intelligent Bots LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-07-01 至 2013-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1214817&HistoricalAwards=false
• 关键词: SBIR; Phase; Novel; Human; Robot

This Small Business Innovation Research (SBIR) Phase I project advances artificial intelligence (AI) and robotics by developing the foundation for emotionally responsive systems. Building on Theory of Mind research in psychology and robotics, this project focuses on enhancing a robot's capacity to integrate two pieces of information in order to determine a third piece. These inferences can be concrete or as abstract as conjectures about another agent's - including a human user's -beliefs, desires, and intentions. The project creates a framework for the robot's AI system to maintain several competing models of the world (particles) and select and modify those models that have a higher likelihood of matching the real world (filtering). This method of "Particle Filtering" is an effective strategy or navigating complex environments. The core research focuses on adapting and assessing particle filtering methods within abstract contexts including knowledge, emotional, and goal states. If successful, as the robot gains additional information through sensors and language processing, it will adapt its models of the users' emotional state and adjust its interactions accordingly. Essentially, this integrative framework will enable robots to understand human desires and frustrations to find creative solutions in response to those needs. The broader impact/commercial potential of this project is the evolution of an Artificial Intelligence interface that emulates an empathic human-to-human experience. Because the system will represent and track multiple dimensions about a human user, the robot can recognize when a user is confused or frustrated and respond accordingly. This intuitive, naturalistic AI platform has substantial research, education, and therapeutic applications and commercialization channels. With its open source software infrastructure and the relative low-cost of the platform, the initial commercial targets are as a platform for robust Science, Technology, Engineering, and Mathematics (STEM) education and as therapeutic technology for children and adults on the autism spectrum.

这个小型企业创新研究 (SBIR) 第一阶段项目通过开发情感响应系统的基础来推进人工智能 (AI) 和机器人技术。该项目以心理学和机器人学的心智理论研究为基础，重点关注增强机器人整合两条信息以确定第三条信息的能力。 这些推论可以是具体的，也可以是抽象的，如对另一个代理（包括人类用户）的信念、愿望和意图的推测。 该项目为机器人的人工智能系统创建了一个框架，以维护多个相互竞争的世界模型（粒子），并选择和修改那些更有可能与现实世界匹配的模型（过滤）。这种“粒子过滤”方法是一种有效的策略或导航复杂环境。核心研究侧重于在抽象背景（包括知识、情感和目标状态）中调整和评估粒子过滤方法。如果成功，当机器人通过传感器和语言处理获得额外信息时，它将调整用户情绪状态的模型并相应地调整其交互。 从本质上讲，这种综合框架将使机器人能够理解人类的愿望和挫折，从而找到满足这些需求的创造性解决方案。该项目更广泛的影响/商业潜力是模拟人与人之间的移情体验的人工智能界面的演变。由于系统将表示并跟踪人类用户的多个维度，因此机器人可以识别用户何时感到困惑或沮丧，并做出相应的反应。这个直观、自然的人工智能平台拥有大量的研究、教育、治疗应用和商业化渠道。凭借其开源软件基础设施和相对低成本的平台，最初的商业目标是作为强大的科学、技术、工程和数学 (STEM) 教育的平台，以及作为自闭症谱系儿童和成人的治疗技术。