Tree search and ARC consistency in constraint satisfaction algorithms
Search in Artificial Intelligence
Agents that reduce work and information overload
Communications of the ACM
Collaborative interface agents
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Direct manipulation vs. interface agents
interactions
Readings in information visualization: using vision to think
Readings in information visualization: using vision to think
Principles of mixed-initiative user interfaces
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Enriching buyers' experiences: the SmartClient approach
Proceedings of the SIGCHI conference on Human Factors in Computing Systems
Synthesizing constraint expressions
Communications of the ACM
Visualizing and Modeling Scattered Multivariate Data
IEEE Computer Graphics and Applications
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Visage: a user interface environment for exploring information
INFOVIS '96 Proceedings of the 1996 IEEE Symposium on Information Visualization (INFOVIS '96)
Automated design of virtual worlds for visualizing multivariate relations
VIS '92 Proceedings of the 3rd conference on Visualization '92
Task allocation via coalition formation among autonomous agents
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Usability guidelines for interactive search in direct manipulation systems
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Qualitative reasoning model for tradeoff analysis
MDAI'05 Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence
Categorization of pictures in tasks of the bebras contest
ISSEP'13 Proceedings of the 6th international conference on Informatics in Schools: Situation, Evolution, and Perspectives
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Visual thinking tools are visualization-enabled mixed initiative systems that empower people in solving complex problems by engaging them in the entire resolution process, suggesting appropriate actions with visual cues, and reducing their cognitive load with visual representations of their tasks. At the same time, the visual interaction style provides an alternative to the dialog-based model employed in most mixed-initiative (MI) systems. Visual thinking tools avoid complex analyses of turn taking, and put users in control all the time. We are especially interested in implementing visual "affordances" in such systems and present three examples used in COMIND, a visual MI system that we have developed. We show how humans can more effectively concentrate on synthesizing problems, selecting resolution paths that were unseen by the machine, and reformulating problems if solutions cannot be found or are unsatisfactory. We further discuss our evaluation of the techniques at the end of the paper.