Summary of On Computing Plans with Uniform Action Costs, by Alberto Pozanco et al.
On Computing Plans with Uniform Action Costs
by Alberto Pozanco, Daniel Borrajo, Manuela Veloso
First submitted to arxiv on: 15 Feb 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 The paper introduces a novel approach to automated planning, focusing on generating plans with uniform action costs. The authors adapt three uniformity metrics to planning problems, allowing for lexicographically optimizing both sum of action costs and action costs uniformity. Experimental results demonstrate the effectiveness of this approach in solving real-world planning tasks, including well-known benchmarks and new challenges. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps planning tools make better suggestions for humans by creating plans with consistent costs. Imagine you’re trying to decide what to do each day: having a routine can be reassuring! The researchers developed new ways to measure how uniform plans are and showed that their approach works well in practice, even on complex problems. |
