Downloads · 30 days
0
walker2d-calibrated-v2
rijal028/walker2d-calibrated-v2
walker2d-calibrated-v2 is a reinforcement learning model from rijal028. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product.
Model policy adaptif bipedal locomotion terkalibrasi yang menggabungkan: - Intrinsically Robust Feedforward Actor (hasil konsolidasi LR $3.0\times 10^{-5}$). - Filtered World Dynamics Anomaly Detector (Threshold: 8.0,…
Access
Public
Updated Aug 23, 2026
Repo size
968 KB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.pt968 KB · 100%
At a glance
- Task
- Reinforcement Learning
- Access
- Public
- Created
- Aug 23, 2026
- Updated
- Aug 23, 2026
- SHA
- eabbf727
Model card
From the Hugging Face model README
Walker2d Calibrated Autonomous Reflective Agent (v2.1)
Model policy adaptif bipedal locomotion terkalibrasi yang menggabungkan:
- Intrinsically Robust Feedforward Actor (hasil konsolidasi LR $3.0\times 10^{-5}$).
- Filtered World Dynamics Anomaly Detector (Threshold: 8.0, Persistence: 3 frames).
- Online Critic-Guided Action Reflection Engine ($lpha = 2.0\times 10^{-3}$, 8 iterations).
Benchmark Highlights (1.000 Steps Suite)
- External Wind Gust (+140N Push): 1.000 steps penuh (+26.14 m) dengan hanya 5 trigger presisi (vs Baseline jatuh di step 367).
- Right Knee Jammed (0 Nm): Tembus 515 steps murni feedforward tanpa false alarm saat fase lari normal.
- Task
- Reinforcement Learning
- Created
- Aug 23, 2026
- Updated
- Aug 23, 2026