This is an implementation of Deep Reinforcement Learning algorithm named Deep determinsitic Policy Gradient (DDPG) to train a 4 DOF robotic Arm to reach the moving target. The action space is continous and the learned agent outputs the torque for the robot to move to the specific target location.
active 2024-05-26 → 2025-07-16 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 417 days from 2024-05-26 to 2025-07-16. Pushes: 0 total, peak 0 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 6 total, peak 1 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
Nobody pushed, opened or commented here in the loaded window — this repo's activity is stars and forks only.
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 6 stars here means stars gained during the window, not the repo's star count.