Decision Oriented Technique (DOTechnique): Finding Model Validity Through Decision-Maker Context
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866911213542178816 |
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| author | Biglari, Raheleh Denil, Joachim |
| author_facet | Biglari, Raheleh Denil, Joachim |
| contents | Model validity is as critical as the model itself, especially when guiding decision-making processes. Traditional approaches often rely on predefined validity frames, which may not always be available or sufficient. This paper introduces the Decision Oriented Technique (DOTechnique), a novel method for determining model validity based on decision consistency rather than output similarity. By evaluating whether surrogate models lead to equivalent decisions compared to high-fidelity models, DOTechnique enables efficient identification of validity regions, even in the absence of explicit validity boundaries. The approach integrates domain constraints and symbolic reasoning to narrow the search space, enhancing computational efficiency. A highway lane change system serves as a motivating example, demonstrating how DOTechnique can uncover the validity region of a simulation model. The results highlight the potential of the technique to support finding model validity through decision-maker context. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_13858 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Decision Oriented Technique (DOTechnique): Finding Model Validity Through Decision-Maker Context Biglari, Raheleh Denil, Joachim Artificial Intelligence I.6.4 Model validity is as critical as the model itself, especially when guiding decision-making processes. Traditional approaches often rely on predefined validity frames, which may not always be available or sufficient. This paper introduces the Decision Oriented Technique (DOTechnique), a novel method for determining model validity based on decision consistency rather than output similarity. By evaluating whether surrogate models lead to equivalent decisions compared to high-fidelity models, DOTechnique enables efficient identification of validity regions, even in the absence of explicit validity boundaries. The approach integrates domain constraints and symbolic reasoning to narrow the search space, enhancing computational efficiency. A highway lane change system serves as a motivating example, demonstrating how DOTechnique can uncover the validity region of a simulation model. The results highlight the potential of the technique to support finding model validity through decision-maker context. |
| title | Decision Oriented Technique (DOTechnique): Finding Model Validity Through Decision-Maker Context |
| topic | Artificial Intelligence I.6.4 |
| url | https://arxiv.org/abs/2510.13858 |