Tom Williams and Evan Krause and Bradley Oosterveld and Matthias Scheutz
Robotics: Science and Systems Workshop on Models and Representations for Natural Human-Robot Communication
Robots participating in natural dialogue may need to discuss, reason about, or initiate actions concerning dialogue-referenced entities. To do so, the robot must first identify or create new representations for those entities, a capability known as reference resolution. We previously presented GH-POWER: an algorithm that used a Givenness Hierarchy theoretic approach to resolving definite, indefinite, anaphoric, and deictic noun phrases in uncertain and open worlds. In this work, we introduce GROWLER: a new reference resolution algorithm which enables more robust reference resolution by extending GH-POWER with a model of relevance, and discuss how this extension is able to handle some cases not handled by our original algorithm.