Target Seeking Tank Using Unity ML-Agents
Channel:
Subscribers:
553
Published on ● Video Link: https://www.youtube.com/watch?v=0u4tmAvqT-k
Demo of machine learning in Unity using ML-Agents. This tank is trained to seek out the blue target box and drive within 2m of it. This is part of an ongoing development for System Intrusion to use machine learning for enemy AI instead of a hard-coded solution. Next steps are to add ML to shoot and hit the target instead of driving to it, and finally to introduce a second tank for adversarial training.
Written in Unity 2019 and using ML-Agents available at the link below:
https://github.com/Unity-Technologies/ml-agents
"Beauty Flow" Kevin MacLeod (incompetech.com)
Licensed under Creative Commons: By Attribution 4.0 License
http://creativecommons.org/licenses/by/4.0/
Other Videos By Jasconius Interactive
2022-11-24 | Do more lines of dialog make for a better game? |
2022-11-17 | Dev Log #3 - New Controller and an Old Game |
2022-11-10 | Dev Log #2 - Third Person Multiplayer |
2022-11-07 | Rant: Gotham at 30fps |
2022-11-03 | Dev Log #1 - Catching up |
2021-06-13 | Planet Testing |
2021-05-08 | Procedural Globular Cluster Prototype 2 |
2021-04-29 | Procedural Globular Cluster (Prototype) |
2020-11-17 | Target Seeking Tank - Revision 4 |
2020-10-26 | Target Seeking Tank - Revision 3 |
2020-10-16 | Target Seeking Tank Using Unity ML-Agents |
2020-09-23 | Donut Special - Dev Timelapse |
2020-09-07 | Blueberry Dev Timelapse |
2020-09-04 | HDRP Marble Demo 2 |
2020-09-04 | HDRP Marble Demo |
2020-07-19 | Stupid Robots Shooting at Targets |
2020-07-10 | Triple TriJam Dev Timelapse |
2020-05-10 | BouncyBlocks - DOTS Test with Havoc Physics |
2020-04-23 | Virtual Fish Tank - Graphics and Balancing |
2020-04-19 | Ludum Dare 46 - Gameplay and two dead fish |
2020-04-19 | Ludum Dare 46 - Food, Medicine, and Tank Cleaning |