Summary of Is Value Functions Estimation with Classification Plug-and-play For Offline Reinforcement Learning?, by Denis Tarasov et al.
Is Value Functions Estimation with Classification Plug-and-play for Offline Reinforcement Learning?
by Denis Tarasov, Kirill Brilliantov, Dmitrii Kharlapenko
First submitted to arxiv on: 10 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 In a departure from traditional reinforcement learning (RL) approaches, researchers have explored using cross-entropy classification objectives instead of mean squared error regression. This shift has shown improved performance and scalability, but its effects across various domains are still largely unexplored. Our study aims to investigate the impact of this replacement in offline RL settings, analyzing how different aspects influence performance. We conducted large-scale experiments across a range of tasks using diverse algorithms, revealing that incorporating this change can lead to superior performance for some algorithms in certain tasks, while maintaining comparable levels for others. However, for other algorithms, this modification resulted in significant performance drops. These findings are essential for the application of classification approaches in both research and practical contexts. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Researchers have found a new way to make reinforcement learning (RL) better. Instead of using mean squared error regression, they’re trying cross-entropy classification objectives. This has worked well so far, but nobody knows how it will do across different areas of study. The team behind this project wanted to find out, so they did lots and lots of experiments with different algorithms and tasks. What they found was that sometimes this new way works really well, and sometimes it doesn’t work as well. This is important for people who want to use RL in real-life situations. |
Keywords
» Artificial intelligence » Classification » Cross entropy » Regression » Reinforcement learning
