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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2026
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| Online-Zugang: | https://arxiv.org/abs/2601.10768 |
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| _version_ | 1866909991962673152 |
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| author | Bočková, Nina Volná, Barbora Dohnal, Mirko |
| author_facet | Bočková, Nina Volná, Barbora Dohnal, Mirko |
| contents | This paper investigates complex product-innovation processes using models grounded in a set of heuristics. Each heuristic is expressed through simple trends -- increasing, decreasing, or constant -- which serve as minimally information-intensive quantifiers, avoiding reliance on numerical values or rough sets. A solution to a trend model is defined as a set of scenarios with possible transitions between them, represented by a transition graph. Any possible future or past behaviour of the system under study can thus be depicted by a path within this graph. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_10768 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Optimisation of complex product innovation processes based on trend models with three-valued logic Bočková, Nina Volná, Barbora Dohnal, Mirko Artificial Intelligence Optimization and Control 34C60, 91B06, 68Q85 This paper investigates complex product-innovation processes using models grounded in a set of heuristics. Each heuristic is expressed through simple trends -- increasing, decreasing, or constant -- which serve as minimally information-intensive quantifiers, avoiding reliance on numerical values or rough sets. A solution to a trend model is defined as a set of scenarios with possible transitions between them, represented by a transition graph. Any possible future or past behaviour of the system under study can thus be depicted by a path within this graph. |
| title | Optimisation of complex product innovation processes based on trend models with three-valued logic |
| topic | Artificial Intelligence Optimization and Control 34C60, 91B06, 68Q85 |
| url | https://arxiv.org/abs/2601.10768 |