A central problem in grounded language acquisition is learning the correspondences
between a rich world state and a stream of text which references that world state. To deal …

Humans and other animals are able not only to coordinate their actions with their current
sensorimotor state, but also to imagine, plan and act in view of the future, and to realize …

Naturalistic longitudinal recordings of child development promise to reveal fresh
perspectives on fundamental questions of language acquisition. In a pilot effort, we have …

To enable human-robot communication and collaboration, previous works represent
grounded verb semantics as the potential change of state to the physical world caused by …

Current approaches to authoring behavior and dialogue for agents that interact with humans
in virtual environments are labor intensive, yet often yield less robust results than desired in …

Introduction In CoSy, our robots were to be able to interact with human. These interactions
served to help the robot learn more about its environment, or to plan and carry out actions …

While identifying the intention of an utterance has played a major role in natural language
understanding, this work is the first to extend intention recognition to the domain of …

The article presents an implemented model for interpreting situated dialogue, as part of a
system for human-robot interaction. The underlying assumption is that to understand …

Abstract Semantics, the study of meaning, is central to research in Natural Language
Processing (NLP) and many other fields connected to Artificial Intelligence. Nevertheless …

Communication with robots is challenging, partly due to their differences from humans and
the consequent discrepancy in people's mental model of what robots can see, hear, or …