On interaction quality in human-robot interaction

In many complex robotics systems, interaction takes place in all directions between human, robot, and environment. Performance of such a system depends on this interaction, and a proper evaluation of a system must build on a proper modeling of interaction, a relevant set of performance metrics, and a methodology to combine metrics into a single performance value. In this paper, existing models of human-robot interaction are adapted to fit complex scenarios with one or several humans and robots. The interaction and the evaluation process is formalized, and a general method to fuse performance values over time and for several performance metrics is presented. The resulting value, denoted interaction quality, adds a dimension to ordinary performance metrics by being explicit about the interplay between performance metrics, and thereby provides a formal framework to understand, model, and address complex aspects of evaluation of human-robot interaction.Peer ReviewedPostprint (author's final draft

Natural Language Communication with Social Robots for Assisted Living

We explore a new dialogue modelling approach for assistive social robots that enables us to formalize flexible conversation flows between a robot and a human. We achieve this by introducing an expectation mechanism to handle, for example, topic change, clarification questions or misunderstandings during a dialogue. The model gave us insight into the dialogue structure and how it is shaped by several linguistic and pragmatic features. This is work in progress and in the future we will explore learning algorithms that mine the features, implement and validate the model with real conversations.

Millstream Systems

We introduce Millstream systems, a mathematical framework in the tradition of the Theory of Computation that uses logic to formalize the interfaces between different aspects of language, the latter being described by any number of independent modules. Unlike other approaches that serve a similar goal, Millstream systems neither presuppose nor establish a particular linguistic theory or focus, but can be instantiated in various ways to accomodate different points of view

Millstream Systems

We introduce Millstream systems, a mathematical framework in the tradition of the Theory of Computation that uses logic to formalize the interfaces between different aspects of language, the latter being described by any number of independent modules. Unlike other approaches that serve a similar goal, Millstream systems neither presuppose nor establish a particular linguistic theory or focus, but can be instantiated in various ways to accomodate different points of view

Natural Language Communication with Social Robots for Assisted Living

We explore a new dialogue modelling approach for assistive social robots that enables us to formalize flexible conversation flows between a robot and a human. We achieve this by introducing an expectation mechanism to handle, for example, topic change, clarification questions or misunderstandings during a dialogue. The model gave us insight into the dialogue structure and how it is shaped by several linguistic and pragmatic features. This is work in progress and in the future we will explore learning algorithms that mine the features, implement and validate the model with real conversations.

Understandable robots - What, Why, and How

As robots become more and more capable and autonomous, there is an increasing need for humans to understand what the robots do and think. In this paper, we investigate what such understanding means and includes, and how robots can be designed to support understanding. After an in-depth survey of related earlier work, we discuss examples showing that understanding includes not only the intentions of the robot, but also desires, knowledge, beliefs, emotions, perceptions, capabilities, and limitations of the robot. The term understanding is formally defined, and the term communicative actions is defined to denote the various ways in which a robot may support a human’s understanding of the robot. A novel model of interaction for understanding is presented. The model describes how both human and robot may utilize a first or higher-order theory of mind to understand each other and perform communicative actions in order to support the other’s understanding. It also describes simpler cases in which the robot performs static communicative actions in order to support the human’s understanding of the robot. In general, communicative actions performed by the robot aim at reducing the mismatch between the mind of the robot, and the robot’s inferred model of the human’s model of the mind of the robot. Based on the proposed model, a set of questions are formulated, to serve as support when developing and implementing the model in real interacting robots

Extended Uniformly Limited T0L Languages and Mild Context-Sensitivity

We study the fixed membership problem for k-uniformly-limited and propagating ET0L systems (kulEPT0L systems). To this end, the algorithm given in [7] is applied. It follows that kulEPT0L languages are parsable in polynomial time. Since kulEPT0L languages are semi-linear [1] and kulEPT0L systems generate certain non-context-free languages, which capture the non-context-free phenomena occurring in natural languages, this is the last building block to show that kulEPT0L languages, for k ≥ 2, belong to the family of mildly context-sensitive languages