An Inference-based Approach to Dialogue System Design

We present an architecture for spoken dialogue systems where first-order inference (both theorem proving and model building) plays a crucial role in interpreting utterances of dialogue participants and deciding how the system should respond and carry out instructions. The dialogue itself is represented as a DRS which is translated into first-order logic for inference tasks. The system is implemented as a society of OAA-agents, and evaluated against a specific application (home automation).