12th Annual Conference of the International Speech Communication Association

Florence, Italy
August 27-31. 2011

Optimizing Situated Dialogue Management in Unknown Environments

Heriberto Cuayáhuitl (1), Nina Dethlefs (2)

(1) DFKI GmbH, Germany
(2) Universität Bremen, Germany

We present a conversational learning agent that helps users navigate through complex and challenging spatial environments. The agent exhibits adaptive behaviour by learning spatially-aware dialogue actions while the user carries out the navigation task. To this end, we use Hierarchical Reinforcement Learning with relational representations to efficiently optimize dialogue actions tightly-coupled with spatial ones, and Bayesian networks to model the user's beliefs of the navigation environment. Since these beliefs are continuously changing, we induce the agent's behaviour in real time. Experimental results, using simulation, are encouraging by showing efficient adaptation to the user's navigation knowledge, specifically to the generated route and the intermediate locations to negotiate with the user.

Full Paper

Bibliographic reference.  Cuayáhuitl, Heriberto / Dethlefs, Nina (2011): "Optimizing situated dialogue management in unknown environments", In INTERSPEECH-2011, 1009-1012.