AI Bibliography
AI Bibliography |
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Attfield, S., & Baber, C. 2017, Elaborating the frames of data-frame theory. Paper presented at 13th International conference on Naturalistic Decision Making. |
| Resource type: Proceedings Article BibTeX citation key: Attfield2017 View all bibliographic details  |
Categories: Artificial Intelligence, Cognitive Science, Complexity Science, Computer Science, Data Sciences, Decision Theory, General, Neuroscience Subcategories: Decision making, Human decisionmaking, Neurosymbolic Creators: Attfield, Baber Publisher: The University of Bath Collection: 13th International conference on Naturalistic Decision Making |
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As an explanation of sensemaking, data-frame theory has proven to be popular, influential and useful. Despite its strengths however, we propose some weaknesses in the way that the concept of a ‘frame’ could be interpreted. The weaknesses relate to a need to clearly contrast what we refer to as ‘generic’ vs. ‘situation-specific’ belief structures and the idea that multiple generic belief structures may be utilized in the construction of embedded situation-specific beliefs. Neither weakness is insurmountable, and we propose a model of sensemaking based on the idea of spreading activation through associative networks as a concept that provides a solution to this. We explore the application of this idea using the notion of activation to differentiate generic from situation specific beliefs.
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