Probabilistic multiparty dialogue management for a game master robot

  • Authors:

  • Casey Kennington;Kotaro Funakoshi;Yuki Takahashi;Mikio Nakano

  • Affiliations:

  • Bielefeld University, CITEC, Bielefeld, Germany;Honda Research Institute Japan Co., Ltd., Wako, Japan;Waseda University, Tokyo, Japan;Honda Research Institute Japan Co., Ltd., Wako, Japan

  • Venue:
  • Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction
  • Year:
  • 2014

Quantified Score

Hi-index 0.00

Visualization

Abstract

We present our ongoing research on multiparty dialogue management for a game master robot which engages multiple human participants to play a quiz game. The robot invites passing people to join the game, instructs participants on the rules of the game, and leads them in the game. The robot has to manage people leaving and coming at arbitrary times. Our approach maintains a dialogue manager for each participant, and a module takes a final action with each decision cycle; responsible to decide "what/whom/when to say". We have implemented the dialogue manager with a probabilistic rules approach [4] and made preliminary evaluations with our multiparty human-robot game dialogue data that was collected in a WoZ fashion.