The role of hierarchical knowledge representation in decisionmaking and system management
Abstract
The knowledge representation of a decision-maker in control of a complex system can be structured in several levels of abstraction in a functional hierarchy. The role of such an abstraction hierarchy in supervisory systems control is reviewed, and the difference between causal and intentional systems and formal games is discussed in terms of the role of an abstraction hierarchy in the related decision strategies. This relationship is then discussed with reference to the classical psychological problem-solving research of O. Selz (1922) and others. Finally, the implications for the design of decision-support systems are discussed. It is argued that an explicit description of the functional properties of the system to be controlled in terms of an abstraction hierarchy is necessary for a consistent design of databases and display formats for decision-support systems. Also, it is necessary to consider the role of the abstraction hierarchy in reasoning when planning experiments on human decision-making.
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The abstraction hierarchy belongs to the class of stratified hierarchies described by Mesarovic, Macko, and Takahara.
“The abstraction hierarchy belongs to the class of stratified hierarchies described by Mesarovic, Macko, and Takahara [58], the properties of which are listed below.”
From Ecological interface design: theoretical foundations (1992) · cites this paper as [58]
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Ecological interface design: theoretical foundations
Vicente, K. J., & Rasmussen, J. (1992) · IEEE Transactions on Systems, Man and Cybernetics · doi:10.1109/21.156574 · Cited by 1,084 · see citing works
Self-citationKhastgir, S., Birrell, S., Dhadyalla, G., & Jennings, P. (2018) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2018.07.001 · Cited by 134 · see citing works
Psychological foundations of explainability and interpretability in artificial intelligence
Broniatowski, D. A. (2021) · doi:10.6028/nist.ir.8367 · Cited by 76 · see citing works
Desai, S., & Chin, J. (2020) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1071181320641112 · Cited by 9 · see citing works
Doi, T. (2021) · Symmetry · doi:10.3390/sym13050795 · Cited by 8 · see citing works
- Authors
- Rasmussen, J.
- Corresponding author
- Rasmussen, Jens
- Venue
- IEEE Transactions on Systems, Man, and Cybernetics
- Published
- 1985-03
- Volume
- SMC-15
- Issue
- 2
- Pages
- 234-243
- ISSN
- 0018-9472 (ISSN-L)
- 2168-2909
- OpenAlex
- W2153294923
- Cited by
- 596
- References
- 0
- Citations by year
- 2026: 27 · 2025: 16 · 2024: 15 · 2023: 19 · 2022: 14 · 2021: 22 · 2020: 15 · 2019: 41 · 2018: 21 · 2017: 19 · 2016: 24 · 2015: 15 · 2014: 18 · 2013: 17 · 2012: 15
- FWCI
- 12.80
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Systems Man and Cybernetics (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › AI-based Problem Solving and Planning
- Social Sciences › Decision Sciences › Management Science and Operations Research › Complex Systems and Decision Making
- Social Sciences › Business, Management and Accounting › Management Information Systems › Decision Support System Applications
- Keywords
- hierarchical knowledge representation, abstraction hierarchy, decision-making, supervisory control system, complex systems, causal systems, intentional systems, decision strategies, problem solving, decision support system, database design, display format, human decision-making, planning experiments
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