Summary of Extended Version Of: on the Structural Hardness Of Answer Set Programming: Can Structure Efficiently Confine the Power Of Disjunctions?, by Markus Hecher et al.
Extended Version of: On the Structural Hardness of Answer Set Programming: Can Structure Efficiently Confine the Power of Disjunctions?
by Markus Hecher, Rafael Kiesel
First submitted to arxiv on: 5 Feb 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 In this paper, researchers tackle the challenge of solving complex problems using Answer Set Programming (ASP), a framework that focuses on knowledge representation and has seen rapid growth in industrial applications. To better understand the complexity of these problems, the study provides insights into hardness, sources of hardness, and detailed parameterized complexity landscapes. However, the authors note that certain parameters, such as treewidth, can lead to double-exponential runtime under reasonable assumptions, making it impractical for large-scale problems. To address this issue, the researchers propose a classification system for structural parameters in disjunctive ASP based on the program’s rule structure (incidence graph). |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Solving complex problems is like finding the right answer in a puzzle. The Answer Set Programming (ASP) framework helps us do just that by organizing and representing knowledge in a specific way. But, sometimes these puzzles can get really tough, and we need to understand why they’re so hard to solve. In this case, the researchers studied how complex problems are structured and found some patterns that help us better understand their difficulty. They also came up with a new way to classify certain types of problem structures, which might make it easier to solve them in the future. |
Keywords
» Artificial intelligence » Classification
