51 citations · 59 across the 4 of their papers we have counts for
6 papers
Probabilistic Plan Legibility with Off-the-shelf Planners
Michele Persiani, Thomas Hellström
Legible planning is the creation of plans that best disambiguate their goals from a set of other candidates from an observer's perspective. In this paper we propose a method for le…
The Mirror Agent Model: a Bayesian Architecture for Interpretable Agent Behavior
Michele Persiani, Thomas Hellström
In this paper we illustrate a novel architecture generating interpretable behavior and explanations. We refer to this architecture as the Mirror Agent Model because it defines the…
The experience of humans' and robots' mutual (im)politeness in enacted service scenarios: An empirical study
Victor Kaptelinin, Suna Bensch, Thomas Hellström +2
The paper reports an empirical study of the effect of human treatment of a robot on the social perception of the robot's behavior. The study employed an enacted interaction between…
Tell Me Why You Feel That Way: Processing Compositional Dependency for Tree-LSTM Aspect Sentiment Triplet Extraction (TASTE)
A. Sutherland, S. Bensch, T. Hellström +2
Sentiment analysis has transitioned from classifying the sentiment of an entire sentence to providing the contextual information of what targets exist in a sentence, what sentiment…
Conversational Norms for Human-Robot Dialogues
Maitreyee Tewari, Thomas Hellström, Suna Bensch
This paper describes a recently initiated research project aiming at supporting development of computerised dialogue systems that handle breaches of conversational norms such as th…
Bias in Machine Learning -- What is it Good for?
Thomas Hellström, Virginia Dignum, Suna Bensch
In public media as well as in scientific publications, the term \emph{bias} is used in conjunction with machine learning in many different contexts, and with many different meaning…