Principles of Mixed-Initiative User Interfaces

Eric Horvitz

Decision Theory & Adaptive Systems Group
Microsoft Research
Redmond, Washington 98052-6399

Access postscript or pdf file.

Abstract:

Recent debate has centered on the relative promise of focusing user-interface research on developing new metaphors and tools that enhance users' abilities to directly manipulate objects versus directing effort toward developing interface agents that provide automation. In this paper, we review principles that show promise for allowing engineers to enhance human-computer interaction through an elegant coupling of automated services with direct manipulation. Key ideas will be highlighted in terms of the Lookout system for scheduling and meeting management.

Keywords: Human-computer interface, goal recognition, user modeling, intelligent agents, direct manipulation, probability, decision theory, user interface design.

In: Proceedings of CHI '99, ACM SIGCHI Conference on Human Factors in Computing Systems, Pittsburgh, PA, May 1999. ACM Press. pp 159-166.

Author Email: horvitz@microsoft.com

Related articles


• E. Horvitz. Uncertainty, Action, and Interaction: In Pursuit of Mixed-Initiative Computing. Intelligent Systems, September 1999, IEEE Computer Society.
  
  
• E. Horvitz and T. Paek, A Computational Architecture for Conversation. Proceedings of the Seventh International Conference on User Modeling, Banff, Canada, June 1999. New York: Springer Wien, pp. 201-210.
  
  
• E. Horvitz and T. Paek. Harnessing Models of Users' Goals to Mediate Clarification Dialog in Spoken Language Systems. Proceedings of the Eighth International Conference on User Modeling, July 2001.
  
  
• E. Horvitz, C. M. Kadie, T. Paek, D. Hovel. Models of Attention in Computing and Communications: From Principles to Applications, Communications of the ACM 46(3):52-59, March 2003.
  
  
• E. Horvitz and T. Paek. Complementary Computing: Policies for Transferring Callers from Dialog Systems to Human Receptionists. User Modeling and User Adapted Interaction 17 (2007).
  
  
• E. Horvitz, P. Koch, R. Sarin, J. Apacible, M. Subramani. Bayesphone: Context-Sensitive Policies for Inquiry and Action in Mobile Devices. Proceedings of the Tenth Conference on User Modeling (UM 2005), July 2005, Edinburgh, Scotland.
  
  
• T. Paek and E. Horvitz, Uncertainty, Utility, and Misunderstanding: A Decision-Theoretic Perspective on Grounding in Conversational Systems. AAAI Fall Symposium on Psychological Models of Communication in Collaborative Systems, Cape Cod, MA. November 5-7, 1999.
  
  
• T. Paek and Eric Horvitz. Conversation as Action Under Uncertainty, In Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence (UAI-2000), Stanford, CA, June 2000.
  
  
• E. Horvitz, J. Breese, D. Heckerman, D. Hovel, and K. Rommelse. The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users. Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, July 1998.
  
  
• Lookout video (1998).
  
  
• Thematic review of several MSR projects in the AI/HCI realm (February 2001).
  
  
• Lookout system's brief debut on a Microsoft television commercial (January 1999).
  

Back to Eric Horvitz's home page.