Mixed‐Initiative Goal Manipulation

Mixed‐initiative planning systems attempt to integrate human and AI planners so that the synthesis results in high‐quality plans. In the AI community, the dominant model of planning is search. In state‐space planning, search consists of backward and forward chaining through the effects and precondit...

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Bibliographic Details
Published in:The AI magazine 2007-06, Vol.28 (2), p.62-73
Main Authors: Cox, Michael T., Zhang, Chen
Format: Article
Language:English
Subjects:
Alternatives
Artificial intelligence
Automation
Computer science
Goal setting
Human-machine systems
Integrated approach
Interfaces
Methods
Planning
User interface
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Summary:Mixed‐initiative planning systems attempt to integrate human and AI planners so that the synthesis results in high‐quality plans. In the AI community, the dominant model of planning is search. In state‐space planning, search consists of backward and forward chaining through the effects and preconditions of operator representations. Although search is an acceptable mechanism to use in performing automated planning, we present an alternative model to present to the user at the interface of a mixed‐initiative planning assistant. That is, we propose to model planning as a goal‐manipulation task. Here planning involves moving goals through a hyperspace in order to reach equilibrium between available resources and the constraints of a dynamic environment. The users can establish and “steer” goals through a visual representation of the planning domain. They can associate resources with particular goals and shift goals along various dimensions in response to changing conditions as well as change the structure of previous plans. Users need not know the details of the underlying technology, even when search is used within. This article empirically examines user performance under both the search and the goal‐manipulation models of planning and shows that many users do better with the latter.
ISSN:0738-4602
2371-9621
DOI:10.1609/aimag.v28i2.2040