Summary of Pruning Boolean D-dnnf Circuits Through Tseitin-awareness, by Vincent Derkinderen
Pruning Boolean d-DNNF Circuits Through Tseitin-Awareness
by Vincent Derkinderen
First submitted to arxiv on: 25 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Logic in Computer Science (cs.LO)
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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 The paper explores Boolean circuits in d-DNNF form for tractable probabilistic inference, but reveals that common compilation approaches introduce unnecessary subcircuits. Dubbed “Tseitin artifacts,” these subcircuits arise from the Tseitin transformation step and can be detected and removed to produce more concise circuits. The study demonstrates an average size reduction of 77.5% when removing both Tseitin variables and artifacts, with additional pruning reducing the size by 22.2%. This improvement has significant implications for downstream tasks that rely on succinct circuits, such as probabilistic inference. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Boolean circuits in d-DNNF form are used to make predictions more efficiently. But when we try to use these circuits, we find that they’re often too big and contain extra parts that aren’t actually needed. These extra parts come from a process called the Tseitin transformation. By getting rid of them, we can make our circuits smaller and more efficient. This is important because smaller circuits are better for tasks like making predictions about things that might happen in the future. |
Keywords
» Artificial intelligence » Inference » Pruning
