Summary of Generalising Planning Environment Redesign, by Alberto Pozanco et al.
Generalising Planning Environment Redesign
by Alberto Pozanco, Ramon Fraga Pereira, Daniel Borrajo
First submitted to arxiv on: 12 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 proposes a general approach to planning environment redesign, departing from traditional methods focused on simplifying goal recognition. Instead, it develops a metric-agnostic method that leverages top-quality planning to efficiently redesign environments according to any objective or metric. This allows for generalization across different objectives and metrics, overcoming limitations of previous approaches. The approach is evaluated through experiments on various environment redesign benchmarks, demonstrating improved performance compared to existing methods. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper wants to make it easier to change the environment in a way that helps someone achieve their goals. Right now, people try to find the simplest changes that make it easy for others to recognize what they want to do. This approach works well if everyone has the same goal or metric, but what if someone’s goal is different? The paper proposes a new method that doesn’t care about recognizing goals and can work with any objective or metric. They tested this method on some examples and found it performs better than current approaches. |
Keywords
» Artificial intelligence » Generalization
