Search Results for author:
Found 4 papers, 0 papers with code
Unsupervised Inference of Object Affordance from Text Corpora
Affordances denote actions that can be performed in the presence of different objects, or possibility of action in an environment.
Policy Regularization for Legible Behavior
To support interpretability in online settings it is useful to borrow from the Explainable Planning literature methods that focus on the legibility of the agent, by making its intention easily discernable in an observer model.
Conversational Norms for Human-Robot Dialogues
This paper describes a recently initiated research project aiming at supporting development of computerised dialogue systems that handle breaches of conversational norms such as the Gricean maxims, which describe how dialogue participants ideally form their utterances in order to be informative, relevant, brief, etc.
Bias in Machine Learning -- What is it Good for?
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 meanings.
