https://github.com/trinkle23897/vizdoom2018-track1
Supplemental materials for "Playing FPS Games with Environment-Aware Hierarchical Reinforcement Learning", accepted by IJCAI'19
https://github.com/trinkle23897/vizdoom2018-track1
hierarchical-reinforcement-learning reinforcement-learning vizdoom-competition
Last synced: 9 months ago
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Supplemental materials for "Playing FPS Games with Environment-Aware Hierarchical Reinforcement Learning", accepted by IJCAI'19
- Host: GitHub
- URL: https://github.com/trinkle23897/vizdoom2018-track1
- Owner: Trinkle23897
- Created: 2019-02-25T14:30:53.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2020-05-14T06:33:26.000Z (over 5 years ago)
- Last Synced: 2025-02-08T23:27:46.231Z (11 months ago)
- Topics: hierarchical-reinforcement-learning, reinforcement-learning, vizdoom-competition
- Homepage: https://www.ijcai.org/proceedings/2019/0482.pdf
- Size: 14.6 MB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Supplemental Materials
### Appendix
Including an experiment "Navigation Task".
### Video Demos
Including 3 demos of ViZDoom single-player sceranios, performed by StarNet.
#### 133.mp4
It first bypasses enemies and picks up some guns, after which it kills all of these enemies within 10 seconds, and finally successfully finishes the game.
#### 56.mp4
It first picks resources, kills two monsters, picks guns, and kills all of enemies.
#### 94.mp4
Almost the same as above.