POPL 2024
Sun 14 - Sat 20 January 2024 London, United Kingdom
Tue 16 Jan 2024 14:00 - 14:30 at Lovelace Room - Answer Set Programming II Chair(s): Mario Alviano

We present the AutoConcierge system that can “understand” human dialogs in a specific domain, namely, restaurant recommendation. AutoConcierge will interactively understand a user’s utterances, and request the user to provide required information via a natural language reply. AutoConcierge uses GPT-3 to convert human dialogs into predicates that represent knowledge implicit in the dialogs. These predicates are then input into the goal-directed s(CASP) answer set programming (ASP) system for performing commonsense reasoning to compute responses in the form of predicates. GPT-3 is used again to convert these computed predicates into natural language sentences that are communicated to the user. To the best of our knowledge, AutoConcierge is the first automated conversational agent that can realistically converse like a human based on truly understanding user utterances. The framework used for AutoConcierge provides a recipe for developing other task-specific chatbots leveraging large language models and answer set programming.

Tue 16 Jan

Displayed time zone: London change

14:00 - 15:30
Answer Set Programming IIPADL at Lovelace Room
Chair(s): Mario Alviano University of Calabria
Automated Interactive Domain-Specific Conversational Agents that Understand Human Dialogs
Yankai Zeng The University of Texas at Dallas, Abhiramon Rajasekharan The University of Texas at Dallas, Parth Padalkar THE UNIVERSITY OF TEXAS AT DALLAS, Kinjal Basu IBM, Joaquín Arias Universidad Rey Juan Carlos, Gopal Gupta University of Texas at Dallas
Forgetting Techniques for Optimizing ASP-based Stream Reasoning
Francesco Calimeri University of Calabria, Giovambattista Ianni University of Calabria, Italy, Francesco Pacenza Department of Mathematics and Computer Science, University of Calabria, Simona Perri University of Calabria, Italy, Jessica Zangari Università della Calabria