Computational Models of Mixed-Initiative Interaction, Reprinted from USER MODELING AND USER-ADAPTED INTERACTION, 8:3-4; 9:1-2, 1999

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.

Preface; S. Haller, S. McRoy. What is Initiative? R. Cohen, et al. An Evidential Model for Tracking Initiative in Collaborative Dialogue Interactions; J. Chu-Carroll, M.K. Brown. An Analysis of Initiative Selection in Collaborative Task-Oriented Discourse; C.I. Guinn. COLLAGEN: A Collaboration Manager for Software Interface Agents; C. Rich, C. Sidner. Lifelike Pedagogical Agents for Mixed-initiative Problem Solving in Constructivist Learning Environments; J.C. Lester, et al. Mixed-Initiative Issues in an Agent-Based Meeting Scheduler; A. Cesta, D. d'Aloisi. Exploring Mixed-Initiative Dialogue Using Computer Dialogue Simulation; M. Ishizaki, et al. A Computational Mechanism for Initiative in Answer Generation; N. Green, S. Carberry. User-Tailored Planning of Mixed Initiative Information-Seeking Dialogues; A. Stein, et al. An Approach to Mixed Initiative Spoken Information Retrieval Dialogue; E. Hagen.