LoopNet v0.2: Reinforcement Learning Trajectories from LoopGym

545 records form this release, combining a seed corpus with captured LoopGym trajectories for LoopNet. The dataset was created by KanakMalpani and was last updated on June 14, 2026. Records conform to the 'ln/record-v1' schema.

Use Cases

• Training reinforcement learning agents based on the captured LoopGym trajectories.
• Benchmarking model performance against a corpus of recorded interactions.
• Analyzing agent behavior patterns from sequential decision-making data.

Strengths

• 545 records provide a defined scale for initial experiments.
• Records conform to a documented schema ('ln/record-v1'), suggesting a structured format.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

LoopGym trajectories and a seed corpus.

Collection Method

Captured trajectories.

Freshness

Last updated 2026-06-14 08:45:05; freshness should be verified.