The Staging Transformation Approach to Mixing Initiative

Mixed-initiative interaction is an important facet of many conversational interfaces, flexible planning architectures, intelligent tutoring systems, and interactive information retrieval systems. Software systems for mixed-initiative interaction must enable us to both operationalize the mixing of initiative (i.e., support the creation of practical dialogs) and to reason in real-time about how a flexible mode of interaction can be supported (e.g., from a meta-dialog standpoint). In this paper, we present the staging transformation approach to mixing initiative, where a dialog script captures the structure of the dialog and dialog control processes are realized through generous use of program transformation techniques (e.g., partial evaluation, currying, slicing); this allows control to be cast as the process of moving from one dialog script to another. In this approach, operationalizing mixed-initiative interaction becomes the task of finding a suitable program transformation to stage the interaction between the two participants. We highlight the advantages of this approach and present its realization in various modalities for information seeking dialogs. We also outline how high-level reasoning capabilities about dialogs can be provided in the staging transformation framework.

[1]  Naren Ramakrishnan PIPE: Web Personalization by Partial Evaluation , 2000, IEEE Internet Comput..

[2]  Naren Ramakrishnan,et al.  Mixed-initiative interaction = mixed computation , 2001, PEPM '02.

[3]  Naren Ramakrishnan,et al.  Personalizing Web sites with mixed-initiative interaction , 2003 .

[4]  K. Tracking Initiative in Collaborative Dialogue Interactions , 2002 .

[5]  Hans Brunner,et al.  An Assessment of Written/Interactive Dialogue for Information Retrieval Applications , 1992, Hum. Comput. Interact..

[6]  David W. Binkley,et al.  Program slicing , 2008, 2008 Frontiers of Software Maintenance.

[7]  Derek G. Bridge,et al.  Towards Conversational Recommender Systems: A Dialogue Grammar Approach , 2002, ECCBR Workshops.

[8]  James F. Allen,et al.  Toward Conversational Human-Computer Interaction , 2001, AI Mag..

[9]  David G. Novick,et al.  What is Mixed-Initiative Interaction? , 1997 .

[10]  David Frohlich,et al.  MIXED INITIATIVE INTERACTION , 1991 .

[11]  Curry Guinn,et al.  Mixed-initiative interaction , 1999 .

[12]  Arthur C. Graesser,et al.  Intelligent Tutoring Systems with Conversational Dialogue , 2001, AI Mag..

[13]  Hiroaki Kitano,et al.  Toward a Plan-Based Understanding Model for Mixed-Initiative Dialogues , 1991, ACL.

[14]  Mary Beth Rosson,et al.  Personalization by Partial Evaluation. , 2001 .

[15]  Mary Beth Rosson,et al.  Explaining Scenarios for Information Personalization , 2001, ArXiv.

[16]  S. Singh,et al.  Optimizing Dialogue Management with Reinforcement Learning: Experiments with the NJFun System , 2011, J. Artif. Intell. Res..

[17]  Peter Sestoft,et al.  Partial evaluation and automatic program generation , 1993, Prentice Hall international series in computer science.

[18]  Neil D. Jones,et al.  An introduction to partial evaluation , 1996, CSUR.

[19]  Andrew G. Clark,et al.  Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL) , 2002 .