SBB Paper Supporting Reinforcement Learning Dataset

A 56.4 KB Excel file provides data supporting the SBB paper. The dataset was authored by Sean Fettrow and last updated in March 2026. Its specific contents and size are detailed in the associated research publication.

Use Cases

• Analyze state-action-reward sequences from the SBB paper's experiments.
• Benchmark reinforcement learning algorithms using the provided environment or agent data.
• Reproduce or validate results from the SBB paper using the underlying experimental records.

Strengths

• Dataset is openly licensed under CC BY 4.0.
• File size of 56.4 KB indicates a focused, manageable scope for analysis.

Limitations

• The dataset is very small at 56.4 KB, limiting its scope and potential for large-scale analysis.
• No column names, sample data, or row count are provided, making preliminary assessment difficult.

Provenance

Source

Sean Fettrow via figshare.

Collection Method

Created to support the SBB research paper; specific collection method unknown.

Freshness

Last updated March 2026.