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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 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:
$15.0万
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
项目状态:
已结题
起止时间:
2012-07-01 至 2013-06-30

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英文摘要
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.
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