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Extending the recognition-primed decision model to support human-agent collaboration
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“(I) Human–human teams generally had better outcomes than did HATs”
From Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature (2022) · cites this paper as Fan et al. (2005)
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Research works printed but not linked: 18
- J. A. Cannon-Bowers, E. Salas, and S. Converse. Cognitive psychology and team training: Training shared mental models and complex systems. Human Factors Society Bulletin, 33:1--4, 1990.
- C. Gonzalez, O. Juarez, and J. Graham. Cognitive and computational models as tools to improve situation awareness. In Proceedings of the 48th Annual Meeting of the Human Factors and Ergonomics Society, 2004.
- E. Hutchins. Cognition in the wild. Cambridge, MA:MIT Press, 1995. · DOI · Paper page
- G. A. Klein. Recognition-primed decisions. In W. B. Rouse, editor, Advances in man-machine systems research, volume 5, pages 47--92. Greenwich, CT: JAI Press, 1989.
- G. A. Klein. Recognition-primed decision making. In Sources of power: How people make decisions, pages 15--30. MIT Press, 1998.
- D. Kleinman, P. Young, and G. Higgins. The DDD-III: A tool for empirical research in adaptive organizations. In Proceedings of the 1996 Command and Control Research and Technology Symposium, 1996.
- 10.5555/267985.268007 · doi:10.5555/267985.268007
- T. LaPorte and P. Consolini. Working in practice but not in theory: Theoretical challenges of high reliability organizations. Journal of public administration research and theory, 1:19--47, 1991.
- J. MacMillan, M. Paley, E. Entin, and E. Entin. Measuring performance in a scaled world: Lessons learned from the distributed dynamic decisionmaking (DDD) synthetic team task. In S. Schiflett, L. Elliott, E. Salas, and M. Coovert, editors, Scaled Worlds: Development, Validation, and Applications. Ashgate Publishing Co., 2004.
- 10.5555/558106 · doi:10.5555/558106
- 10.5555/1018409.1018755 · doi:10.5555/1018409.1018755
- 10.5555/369837.369858 · doi:10.5555/369837.369858
- E. Salas, T. L. Dickinson, S. A. Converse, and S. I. Tannenbaum. Toward an understanding of team performance and training. In R. W. Swezey and E. Salas, editors, Teams: Their training and performance, pages 3--29. Norwood, NJ: Ablex, 1992.
- D. Serfaty, E. Entin, and J. Johnston. Team coordination training. In J. Cannon-Bowers and E. Salas, editors, Making decisions under stress: implications for training and simulation, pages 221--245. APA Press, 1998.
- M. Sierhuis, J. M. Bradshaw, A. Acquisti, R. van Hoof, R. Jeffers, and A. Uszok. Human-agent teamwork and adjustable autonomy in practice. In 7th International Symposium on Artificial Intelligence (I-SAIRAS), NARA, JAPAN, 2003.
- W. Warwick, S. McIlwaine, R. Hutton, and P. McDermott. Developing computational models of recognition-primed decision making. In Proceedings of the tenth conference on Computer Generated Forces, Norfolk, VA., pages 232--331, 2001.
- 10.1016/j.dss.2004.06.008 · DOI
- J. Yen, J. Yin, T. Ioerger, M. Miller, D. Xu, and R. Volz. Cast: Collaborative agents for simulating teamworks. In Proceedings of IJCAI'2001, pages 1135--1142, 2001.
Cited by
Human–Autonomy Teaming: A Review and Analysis of the Empirical Literature
O’Neill, T., McNeese, N., Barron, A., & Schelble, B. (2022) · Human Factors: The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720820960865 · Cited by 695
Metadata
- Authors
- Fan, X., Sun, S., McNeese, M., & Yen, J.
- Affiliations
- The Pennsylvania State University, University Park, PA
- Venue
- Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
- Publisher
- ACM
- Published
- 2005-07-25
- Pages
- 945-952
- Cited by
- 33
- References
- 0
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.