Abstract Purpose of Review As robots become increasingly prevalent and capable, the
complexity of roles and responsibilities assigned to them as well as our expectations for …

Recent progress in deep learning is essentially based on a “big data for small tasks”
paradigm, under which massive amounts of data are used to train a classifier for a single …

For robots to effectively collaborate with humans, it is critical to establish a shared mental
model amongst teammates. In the case of incongruous models, catastrophic failures may …

In this article, we propose a communicative learning (CL) formalism that unifies existing
machine learning paradigms, such as passive learning, active learning, algorithmic …

The potential capacity for robots to deceive has received considerable attention recently.
Many papers explore the technical possibility for a robot to engage in deception for …

Advanced social cognitive skills enhance the effectiveness of human-robot interactions.
Research shows that an important precursor to the development of these abilities in humans …

Recognizing when people have false beliefs is crucial for understanding their actions. We
introduce the novel problem of identifying when people in abstract scenes have incorrect …

Human activity recognition (HAR) deals with recognition of activities or interactions that
include humans within a video. Entities occurring in a video frame can be abstracted in …

The potential capacity for robots to deceive has received considerable attention recently.
Many papers focus on the technical possibility for a robot to engage in deception for …

With the rapid advancements in the field of artificial intelligence (AI) in recent years, one of
the longstanding goals of the field–building AI systems that are able to interact with other …