Skip to Main content Skip to Navigation
Book section

Users' Belief Awareness in Reinforcement Learning-based Situated Human-Robot Dialogue Management

Abstract : Others can have a different perception of the world than ours. Understanding this divergence is an ability, known as perspective taking in developmental psychology, that humans exploit in daily social interactions. A recent trend in robotics aims at endowing robots with similar mental mechanisms. The goal then is to enable them to naturally and efficiently plan tasks and communicate about them. In this paper we address this challenge extending a state-of-the-art goal-oriented dialogue management framework, the Hidden Information State (HIS). The new version makes use of the robot's awareness of the users' belief in a reinforcement learning-based situated dialogue management optimisation procedure. Thus the proposed solution enables the system to cope with the communication ambiguities due to noisy channel but also with the possible misunderstandings due to some divergence among the beliefs of the robot and its interlocutor in a Human-Robot Interaction (HRI) context. We show the relevance of the approach by comparing different handcrafted and learnt dialogue policies with and without divergent belief reasoning in an in-house Pick-Place-Carry scenario by mean of user trials in a simulated 3D environment.
Complete list of metadatas

Cited literature [21 references]  Display  Hide  Download

https://hal.laas.fr/hal-01955213
Contributor : Aurélie Clodic <>
Submitted on : Friday, December 14, 2018 - 11:10:25 AM
Last modification on : Tuesday, January 14, 2020 - 10:38:06 AM
Long-term archiving on: : Friday, March 15, 2019 - 2:17:34 PM

File

2015-iwsds-ferreira.pdf
Files produced by the author(s)

Identifiers

Citation

Emmanuel Ferreira, Grégoire Milliez, Fabrice Lefèvre, Rachid Alami. Users' Belief Awareness in Reinforcement Learning-based Situated Human-Robot Dialogue Management. G.G. Lee, H.K. Kim, M. Jeong, J.-H. Kim. Natural Language Dialog Systems and Intelligent Assistants, Springer International Publishing, pp.73-86, 2015, 978-3-319-19291-8. ⟨10.1007/978-3-319-19291-8_7⟩. ⟨hal-01955213⟩

Share

Metrics

Record views

158

Files downloads

157