Horizon-Adaptive Multi-Turn RL vs Single-Turn PPO in LongNav-R1 Sample Efficiency

This report synthesises findings from 7 peer-reviewed papers addressing the following research question: How does the sample efficiency of horizon-adaptive multi-turn RL in LongNav-R1 compare to single-turn PPO baselines when evaluated on the Habitat-Matterport3D dataset. We present Habitat, a platform for research in embodied artificial intelligence (AI). Habitat enables training embodied agents (virtual robots) in highly efficient photorealistic 3D simulation. 13 claims were extracted from source literature; 13 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 9.3/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research goal: How does the sample efficiency of horizon-adaptive multi-turn RL in LongNav-R1 compare to single-turn PPO baselines when evaluated on the Habitat-Matterport3D dataset?

Autonomous literature synthesis. Automated review score: 9.3/10. Full text and citation available at Assignee Research.