Summary of Automating Reformulation Of Essence Specifications Via Graph Rewriting, by Ian Miguel et al.
Automating Reformulation of Essence Specifications via Graph Rewriting
by Ian Miguel, András Z. Salamon, Christopher Stone
First submitted to arxiv on: 14 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary In this paper, researchers present a novel approach to improve the efficiency of solving parameterized problems by automatically reformulating input models using graph rewriting techniques. The proposed system leverages the Essence abstract constraint specification language to trigger rewrites directly based on high-level variable types. The implementation is done via rewrite rules expressed in Graph Programs 2 language applied to the abstract syntax tree of an input specification. The authors demonstrate the efficacy of their approach with a case study, showcasing how the reformulated problem can be translated back into the original problem for verification and presentation. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Solving problems efficiently is crucial when dealing with parameterized problems. This paper introduces a system that uses graph rewriting to automatically improve model performance. By using the Essence language, the system can rewrite models based on variable types. The authors also show how their approach can be used to verify and present solutions for original problems. Overall, this innovative method can help solve complex problems more efficiently. |
Keywords
» Artificial intelligence » Syntax
