HCC: Small: Social Agents and Robots for Open-Ended Domains

娱乐活动是人类生存的一个基本方面，也是家庭和社会群体中人类状况的重要组成部分，它通过增加个人之间的影响来加强社会联系，并作为创造性思维的一种教育形式。尽管社会学、人类学和心理学关于这类活动的知识积累了相当大的规模，但作为一个一级概念的“游戏”还没有从计算的角度进行研究。当今天的代理与人类接触时，他们是在结构化环境的上下文中进行的，并且高度依赖于定义良好的目标和/或行为。这与假装游戏的领域形成了鲜明对比，后者涉及在不断变化的共享想象第二现实中进行非目标定向的对等活动。假装游戏是一种常见的参与形式，与一系列社交领域有关，如老年人护理、同伴学习或自闭症谱系障碍儿童的社交技能治疗。PI在这项研究中的目标是向机器人系统灌输对游戏的程序性和陈述性表征，以便它们能够与人类作为同龄人进行此类活动。这项工作旨在发现如何开发具有在非结构化环境中与人类互动、即兴创作和创造能力的类人机器人。这样的机器人能力将培养人们对逼真、社会接受度和友谊的看法，类似于与其他人一起玩耍的体验。这些代理人将鼓励人们积极的行为和创造力。它们将引起高度的兴趣、内在的动机和积极的情感，这反过来又会导致人类参与者更好地集中注意力、学习和个人投资。为了实现这些目标，PI将利用他之前在创造力和认知方面的工作，对参与基于对象的假装游戏的成年人进行一项研究，以获得对二元游戏的正式理解。基于该团队在以人为中心的人工智能和人与机器人互动方面的专业知识，这些发现将随后应用于构建参与的社交机器人。将对由此产生的机器人体系结构进行评估，以了解它如何提高机器人的影响力和社会接受度。更广泛的影响：这项研究将在社交机器人领域创造一个新的计算游戏的学术研究方向，有可能为该领域做出坚实而独特的进展，并改变我们与智能代理交互的方式，从而提高代理的社会价值和被周围人接受。这项工作将通过实证研究增加我们对人类参与的理解，特别是对假想场景中涉及的知识和社会动力学的理解。将在这项工作中设计、实施和正式评估的嬉戏机器人将向人-机器人交互社区告知如何在HRI环境中使用这种活动来增加情感。这项工作还有可能改善那些与社会主体互动的人的学习和创造力，使计算发挥作用成为教育的一个有价值的研究方向。该项目将为研究生和本科生的跨学科培训提供肥沃的土壤，并将与科学界共享丰富的互动数据。

Recreational activity is a fundamental aspect of human existence and an important part of the human condition within familial and social groups, where it serves to strengthen social ties by increasing affect between individuals and as a form of education in creative thinking. Despite a sizable accumulation of knowledge about such activity from sociology, anthropology, and psychology, "play" as a first-class concept has not been studied through the lens of computation. When today's agents engage with humans, they do so in the context of structured environments and are highly dependent on well-defined goals and/or behaviors. Contrast this to the domain of pretend play, which involves non-goal directed peer-to-peer activity in a shared imaginary second reality that is continually altered. Pretend play is a common form of engagement that is relevant to an array of social domains, such as elder care, peer learning, or social skills therapy for children with autism spectrum disorders. The PI's goal in this research is to imbue robot systems with procedural and declarative representations of play so that they are capable of engaging in such activity with humans as peers. The work aims to discover how to develop humanoid robots with the ability to engage, improvise, and create with humans in unstructured environments. Such robot capability would foster perceptions of lifelikeness, social acceptance, and companionship similar to the experience of playing with other people. These agents would encourage spirited behaviors and creativity in people. They would elicit high levels of interest, intrinsic motivation, and positive affect, which in turn would lead to better concentration, learning, and personal investment by the human participant. To achieve these goals, the PI will leverage his prior work on creativity and cognition to conduct a study of adults engaging in object-based pretend play to elicit a formal understanding of it in dyads. The findings will subsequently be applied to building social robots that engage, based on the team's expertise in human-centered AI and human-robot interaction. The resulting robot architecture will be evaluated to see how it can enhance robot affect and social acceptance. Broader Impacts: This research will create a new academic research direction of Computational Play within the field of social robotics that has the potential to contribute a solid and unique advance to the field, and also to change how we interact with intelligent agents thereby increasing agents' social value and acceptance by the humans around them. The work will increase via empirical study our understanding of human engagement, and in particular of the knowledge and social dynamics involved in pretend scenarios. The playful robots to be designed, implemented and formally evaluated in this work will inform the human-robot interaction community as to how such activity can be used within HRI contexts to increase affect. This work also has the potential of improving the learning and creativity of those that interact with social agents, making computational play a valuable research direction for education. The project will provide a fertile ground for interdisciplinary training of graduate and undergraduate students, and a wealth of interaction data that will be shared with the scientific community.