Collaboration plays a critical role when a group is striving for goals which are difficult or impossible to achieve by an individual. Knowledge about collaborators' contributions to a task is an important factor when establishing collaboration, in particular when a decision determines the assignment of activities to members of the group. Although there are several systems that implement collaboration, one important problem has not yet received much attention determining the effect of incomplete and uncertain knowledge of collaborators' internal resources (i.e. capabilities and knowledge) on the outcomes of the collaboration. We approach this problem by building models of internal resources of individuals and groups of collaborators. These models enable a system to estimate collaborators' contributions to the task. We then assess the effect of model accuracy on task performance. An empirical evaluation is performed in order to validate this approach. © Springer-Verlag Berlin Heidelberg 2004.
CITATION STYLE
Guttmann, C., & Zukerman, I. (2004). Towards models of incomplete and uncertain knowledge of collaborators’ internal resources. In Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) (Vol. 3187, pp. 58–72). Springer Verlag. https://doi.org/10.1007/978-3-540-30082-3_5
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