Enabling rich human-agent interaction for a calendar scheduling agent

  • Authors:
  • Andrew Faulring;Brad A. Myers

  • Affiliations:
  • Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • CHI '05 Extended Abstracts on Human Factors in Computing Systems
  • Year:
  • 2005

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Abstract

The RhaiCAL system provides novel visualizations and interaction techniques for interacting with an intelligent agent, with an emphasis on calendar scheduling. After an agent interprets natural language containing meeting information, a user can easily correct mistakes using RhaiCAL's clarification dialogs, which provide the agent with feedback to improve its performance. When an agent proposes actions to take on the user's behalf, it can ask the user to confirm them. RhaiCAL uses novel visualizations to present the proposal to the user and allow them to modify the proposal, and informs the agent of the user's actions in a manner that supports long-term learning of the user's preferences. We have designed a high-level XML-based language that allows an agent to express its questions and proposed actions without mentioning user interface details, and that enables RhaiCAL to generate high-quality user interfaces.