Computational Models of Mixed-Initiative Interaction

1. Front Matter

   Pages i-4

   PDF

2. What is Initiative?

   • Dr. Robin Cohen, Coralee Allaby, Christian Cumbaa, Mark Fitzgerald, Kinson Ho, Bowen Hui et al.

   Pages 5-48

3. An Evidential Model for Tracking Initiative in Collaborative Dialogue Interactions

   • Jennifer Chu-Carroll, Michael K. Brown

   Pages 49-87

4. An Analysis of Initiative Selection in Collaborative Task-Oriented Discourse

   • Curry I. Guinn

   Pages 89-148

5. COLLAGEN: A Collaboration Manager for Software Interface Agents

   • Charles Rich, Candace L. Sidner

   Pages 149-184

6. Lifelike Pedagogical Agents for Mixed-Initiative Problem Solving in Constructivist Learning Environments

   • James C. Lester, Brian A. Stone, Gary D. Stelling

   Pages 185-228

7. Mixed-Initiative Issues in an Agent-Based Meeting Scheduler

   • Amedeo Cesta, Daniela D’aloisi

   Pages 229-262

8. Exploring Mixed-Initiative Dialogue Using Computer Dialogue Simulation

   • Masato Ishizaki, Matthew Crocker, Chris Mellish

   Pages 263-275

9. A Computational Mechanism for Initiative in Answer Generation

   • Nancy Green, Sandra Carberry

   Pages 277-316

10. User-Tailored Planning of Mixed Initiative Information-Seeking Dialogues

    • Adelheit Stein, Jon Atle Gulla, Ulrich Thiel

    Pages 317-350

11. An Approach to Mixed Initiative Spoken Information Retrieval Dialogue

    • Eli Hagen

    Pages 351-397

Computational Models of Mixed-Initiative Interaction brings together research that spans several disciplines related to artificial intelligence, including natural language processing, information retrieval, machine learning, planning, and computer-aided instruction, to account for the role that mixed initiative plays in the design of intelligent systems. The ten contributions address the single issue of how control of an interaction should be managed when abilities needed to solve a problem are distributed among collaborating agents.
Managing control of an interaction among humans and computers to gather and assemble knowledge and expertise is a major challenge that must be met to develop machines that effectively collaborate with humans. This is the first collection to specifically address this issue.

• Design
• Interaction
• Interface
• agents
• artificial intelligence
• control
• intelligence
• intelligent systems
• knowledge
• learning
• machine learning
• natural language
• natural language processing
• problem solving
• simulation

• University of Wisonsin-Parkside, Kenosha, USA

  Susan Haller

• German National Research Center for Information Technology, St. Augustin, Germany

  Alfred Kobsa

• University of Wisonsin-Milwaukee, Milwaukee, USA

  Susan McRoy

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