Abstract
Despite the significant demand for assistive technology among vulnerable groups (e.g., the elderly, children, and the disabled) in daily tasks, research into advanced AI-driven assistive solutions that genuinely accommodate their diverse needs remains sparse. Traditional human-machine interaction tasks often require machines to simply help without nuanced consideration of human abilities and feelings, such as their opportunity for practice and learning, sense of self-improvement, and self-esteem. Addressing this gap, we define a pivotal and novel challenge Smart Help, which aims to provide proactive yet adaptive support to human agents with diverse disabilities and dynamic goals in various tasks and environments. To establish this challenge, we leverage AI2-THOR to build a new interactive 3D realistic household environment for the Smart Help task. We introduce an innovative opponent modeling module that provides a nuanced understanding of the main agent's capabilities and goals, in order to optimize the assisting agent's helping policy. Rigorous experiments validate the efficacy of our model components and show the superiority of our holistic approach against established baselines. Our findings illustrate the potential of AI-imbued assistive robots in improving the well-being of vulnerable groups.
Abstract (translated)
尽管在弱势群体（如老年人、儿童和残疾人）在日常任务中寻求辅助技术的需求很大，但研究真正适应他们多样化需求的高级人工智能驱动辅助解决方案仍然很少。传统的人机交互任务通常要求机器仅仅帮助，而没有考虑到人类的能力和感受，比如他们的练习和学习机会、自我提高和自尊心。为了填补这一空白，我们定义了一个重要的、新颖的挑战——智能助手（Smart Help），旨在为具有不同残疾和动态目标的人造智能代理提供主动且适应性的支持。为建立这个挑战，我们利用AI2-THOR构建了一个新的智能助手任务的三维现实家庭环境。我们引入了一种创新的对手建模模块，以提供对主要代理的能动性和目标的有细粒度的理解，从而优化辅助代理的协助策略。严格的实验证实了我们的模型组件的有效性，并表明了我们的整体方法相对于现有基线的优越性。我们的研究结果表明，人工智能辅助机器人在改善弱势群体的生活质量方面具有巨大的潜力。
URL
https://arxiv.org/abs/2404.09001
