| --- |
| license: mit |
| task_categories: |
| - reinforcement-learning |
| - robotics |
| - tabular-classification |
| - time-series-forecasting |
| tags: |
| - timeseries |
| - tabular |
| - robotics |
| - RL |
| - RLHF |
| - reinforcement-learning |
| - experience-replay |
| - state-action-reward |
| - gaming |
| - gym |
| - video-games |
| - games |
| --- |
| |
| [](https://webxos.netlify.app) |
| [](https://github.com/webxos/webxos) |
| [](https://huggingface.co/webxos) |
| [](https://x.com/webxos) |
|
|
| <div style=" |
| background: #00FF00; |
| border-left: 4px solid #00FF00; |
| padding: 1.5rem; |
| margin: 2rem 0; |
| font-family: 'Fira Code', 'Courier New', monospace; |
| color: #00FF00; |
| border-radius: 0 8px 8px 0; |
| "> |
| <pre style=" |
| font-size: 8px; |
| line-height: 1.2; |
| margin: 0; |
| overflow-x: auto; |
| color: #00FF00; |
| "> |
| _____ _ _ ___________ ___________ _____ _____ _ _ |
| / ___| \ | |_ _| ___ \ ___| ___ \ / __ \| ___| | | | |
| \ `--.| \| | | | | |_/ / |__ | |_/ / | / \/| |__ | | | | |
| `--. \ . ` | | | | __/| __|| / | | | __|| | | | |
| /\__/ / |\ |_| |_| | | |___| |\ \ | \__/\| |___| |____| |____ |
| \____/\_| \_/\___/\_| \____/\_| \_| \____/\____/\_____/\_____/ |
| |
| </div> |
| |
| SNIPER CELL - SAMPLE TRAINING DATA EXPORT |
| ============================================= |
| |
| This dataset sample was created with SNIPER CELL by webXOS located in the /gym/ folder, download it to create your own datasets. Sniper cell is a first person |
| shooter based gym that runs minimal in browsers. Users can play the "gym" to record and export training data as seen below. |
|
|
| ### INFO |
| Sample of Sniper Cell Game Data: |
| Exported: 2026-01-08T02:20:14.260Z |
| Player Level: 9 |
| Total XP: 15843 |
| Waves Completed: 3 |
| Drones Destroyed: 22 |
| Accuracy: 21% |
|
|
| FILES INCLUDED: |
| --------------- |
| 1. xforc3d_training_data.json - Complete dataset in JSON format |
| 2. shots_data.csv - All shots fired by player and drones |
| 3. hits_data.csv - All hits and drone destructions |
| 4. level_ups_data.csv - Level progression data |
| 5. waves_data.csv - Wave completion data |
| |
| DATA STRUCTURE: |
| --------------- |
| - Each action is timestamped for time-series analysis |
| - XP rewards and penalties are recorded |
| - Position data for spatial analysis |
| - Level-based difficulty scaling included |
| |
| TIERED DRONE SYSTEM: |
| -------------------- |
| Level 1-10: 4-5 drones max |
| Level 11-20: 6 drones max |
| Level 21-30: 7 drones max |
| Level 31-40: 8 drones max |
| Level 41-50: 9 drones max |
| Level 51-99: 10 drones max |
| |
| USE FOR TRAINING: |
| ----------------- |
| This data can be used to train reinforcement learning models |
| for drone combat AI, player behavior prediction, or |
| difficulty balancing algorithms. |
| |
| COMPRESSION: |
| ------------ |
| This ZIP file supports GZIP, ZSTD, BZ2, LZ4, and LZMA decompression. |