Schema-based dialogue management : from friendly peer to virtual standardized cancer patient

Abstract

Thesis (Ph. D.)--University of Rochester. Department of Computer Science, 2024.Generalist conversational agents are a longstanding goal for dialogue researchers; however, this goal remains elusive owing to the often divergent roles of robust “analogical” reasoning and rigorous formal reasoning in computer dialogue. This dissertation proposes a general dialogue management framework, Eta, for creating conversational agents using an explicit schema representation that subsumes both modes of behavior. The schemas used by Eta represent expected or prototypical dialogue events, and can be used to dynamically guide dialogue through incremental matching of schemas to Eta’s observed dialogue context. Deploying an agent to a particular domain requires only the creation of a set of schemas and the integration of modular, portable pattern transduction methods; the latter allows for the flexible integration of both symbolic methods and large language models in processes such as interpretation, reasoning, planning, and generation. I demonstrate the generality of this approach by presenting a chronology of case studies of conversational agents created using Eta across three highly diverse domains: beginning with a friendly peer for social skill assistance; then turning to a spatially situated collaborative agent in a physical “blocks world” domain; and finally I present a virtual standardized cancer patient for end-of-life communication practice, representing the most elaborate application of Eta to date. I conclude the dissertation by shifting to an empirical investigation of how prototypical knowledge about cognitive attitudes – such as that contained within dialogue schemas – is reflected in natural language itself, laying the groundwork for more precise methods of inference about such event knowledge