Toward Domain-Independent Dialogue Planning

This work was presented at HAIDM 2015. The 2015 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: While the development of techniques that allow artificial agents to engage in dialogue with humans has received a lot of interest in the multiagent systems and natural language processing literature, most of the systems created to date have focused on specific domains and types of dialogue. This has led to agent designs that are useful for specific dialogue situations, but hard to adapt to different settings. The creation of more flexible agents that can deal with a broad range of communicative scenarios would greatly improve the interaction between agents and humans, and would eliminate the need to manually adapt the design of a conversational agent when dealing with a new task domain. In this paper, we present initial work toward creating agents that are able to generate task-oriented dialogues based on a description of a previously unknown domain. Our method is based on utilising automated planning methods, which are suitable for processing specifications both of the communication language to be used and of the domain in hand. We provide preliminary experimental results which suggest that our method has the potential to provide the flexibility required to produce a broad range of communication behaviours in different settings.

Keywords: Dialogue Planning, Conversational Agents, Human-Agent Dialogue.

Citation: Tânia Marques and Michael Rovatsos. Toward Domain-Independent Dialogue Planning.

Download: http://bit.ly/1VzKPg1

About P. Andreadis

Pre-Doctoral Research Assistant in AI and Social Computation @ University of Edinburgh.

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