The Goal-Hypothesis-Experiment framework: A generative cognitive domain architecture for simulation experiment management
Abstract
Simulation experiments are not conducted in a vacuum. They are performed to address specific research questions that require evaluation of testable hypotheses. However, the connections among goals, hypotheses, and experiments are often characterized in an ad hoc manner. In this paper, we examine symbiotic dependencies among goals, hypotheses, and experiments within the context of computational discovery. Model-Driven Science is advanced as a strategy to facilitate the search process within the operational level of hypotheses and the tactical level of experiments. We discuss the theory of explanatory coherence for evaluating and revising hypotheses while using it as a run-time cognitive model that evolves via experimentation toward an explanatory theory of the system under study.
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Cites
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Each entity and activity in the final set has already been mentioned for provenance, modeling or documentation purposes, or experiment design of simulation studies, but they have not all been used together.
“Each entity and activity has already been mentioned for provenance, modeling or documentation purposes, or experiment design of simulation studies [1, 3–5, 8, 20, 21, 60–63], but they have not all been used together.”
From Relating simulation studies by provenance—Developing a family of Wnt signaling models (2021) · cites this paper as [60]
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Relating simulation studies by provenance—Developing a family of Wnt signaling models
Budde, K., Smith, J., Wilsdorf, P., Haack, F., & Uhrmacher, A. M. (2021) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1009227 · Cited by 23 · see citing works
“Each entity and activity has already been mentioned for provenance, modeling or documentation purposes, or experiment design of simulation studies [1, 3–5, 8, 20, 21, 60–63], but they have not all been used together.”
Method
- Authors
- Yilmaz, L., Chakladar, S., & Doud, K.
- Affiliations
- Auburn University (US)
- Venue
- 2016 Winter Simulation Conference (WSC)
- Publisher
- IEEE
- Published
- 2016-12
- Pages
- 1001-1012
- ISSN
- 0891-7736 (ISSN-L)
- OpenAlex
- W4237992927
- Cited by
- 14
- References
- 0
- Citations by year
- 2025: 1 · 2023: 1 · 2022: 3 · 2021: 2 · 2019: 2 · 2018: 2 · 2017: 3
- FWCI
- 3.75
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Winter Simulation Conference (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Simulation Techniques and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Multi-Agent Systems and Negotiation
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Keywords
- computational discovery, explanatory coherence, cognitive models
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
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