Deep Reasoning in Clarification Dialogues with Mobile Robots

Authors:
Cui Jian;Desislava Zhekova;Hui Shi;John Bateman
Affiliations:
University of Bremen, Germany, email: ken@informatik.uni-bremen.de;University of Bremen, Germany, email: zhekova@uni-bremen.de;DFKI Bremen, Germany, email: hui.shi@dfki.de;University of Bremen, Germany, email: bateman@uni-bremen.de
Venue:
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Year:
2010

Citing 8
Cited 0

Spoken natural language dialog systems: a practical approach

Spoken natural language dialog systems: a practical approach
Maintaining knowledge about temporal intervals

Communications of the ACM
Qualitative Spatial Representation and Reasoning with the Region Connection Calculus

Geoinformatica
How Space Structures Language

Spatial Cognition, An Interdisciplinary Approach to Representing and Processing Spatial Knowledge
Modelling Navigational Knowledge by Route Graphs

Spatial Cognition II, Integrating Abstract Theories, Empirical Studies, Formal Methods, and Practical Applications
Enabling technology for multilingual natural language generation: the KPML development environment

Natural Language Engineering
Conceptual spatial representations for indoor mobile robots

Robotics and Autonomous Systems
Deep-reasoning-centred dialogue

ENLG '07 Proceedings of the Eleventh European Workshop on Natural Language Generation

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper reports our work on qualitative reasoning based clarification dialogues in human-robot interaction on spatial navigation. To interpret humans' route instructions, a qualitative spatial model is introduced which represents the robot's beliefs in the application domain. Based on the qualitative spatial model, three tool-supported reasoning strategies are discussed which enable the robot to generate dialogues with differing degrees of clarification if knowledge mismatches or under-specifications in route instructions are detected. The influence of the reasoning strategies on human-robot dialogues is evaluated with an empirical study.