Summary of Puzzles: a Benchmark For Neural Algorithmic Reasoning, by Benjamin Estermann et al.
PUZZLES: A Benchmark for Neural Algorithmic Reasoning
by Benjamin Estermann, Luca A. Lanzendörfer, Yannick Niedermayr, Roger Wattenhofer
First submitted to arxiv on: 29 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI)
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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 PUZZLES, a benchmark for algorithmic and logical reasoning in Reinforcement Learning (RL). It contains 40 diverse logic puzzles with adjustable sizes and complexity levels. The benchmark aims to foster progress in RL agents’ strengths and generalization capabilities. Various RL algorithms are evaluated on PUZZLES, providing baseline comparisons and demonstrating potential for future research. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper creates a new benchmark called PUZZLES to test the ability of Reinforcement Learning (RL) agents to solve logic puzzles. It has 40 puzzles that can be adjusted in size and complexity. The goal is to see how well different RL algorithms do on these puzzles. This will help researchers understand their strengths and weaknesses. |
Keywords
» Artificial intelligence » Generalization » Reinforcement learning
