Towards Human Engagement with Realistic AI Combat Pilots
Fuente:
arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866914067704184832 |
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| author | Selmonaj, Ardian Del Rio, Giacomo Schneider, Adrian Antonucci, Alessandro |
| author_facet | Selmonaj, Ardian Del Rio, Giacomo Schneider, Adrian Antonucci, Alessandro |
| contents | We present a system that enables real-time interaction between human users and agents trained to control fighter jets in simulated 3D air combat scenarios. The agents are trained in a dedicated environment using Multi-Agent Reinforcement Learning. A communication link is developed to allow seamless deployment of trained agents into VR-Forces, a widely used defense simulation tool for realistic tactical scenarios. This integration allows mixed simulations where human-controlled entities engage with intelligent agents exhibiting distinct combat behaviors. Our interaction model creates new opportunities for human-agent teaming, immersive training, and the exploration of innovative tactics in defense contexts. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_26002 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards Human Engagement with Realistic AI Combat Pilots Selmonaj, Ardian Del Rio, Giacomo Schneider, Adrian Antonucci, Alessandro Artificial Intelligence Human-Computer Interaction Machine Learning Multiagent Systems Robotics We present a system that enables real-time interaction between human users and agents trained to control fighter jets in simulated 3D air combat scenarios. The agents are trained in a dedicated environment using Multi-Agent Reinforcement Learning. A communication link is developed to allow seamless deployment of trained agents into VR-Forces, a widely used defense simulation tool for realistic tactical scenarios. This integration allows mixed simulations where human-controlled entities engage with intelligent agents exhibiting distinct combat behaviors. Our interaction model creates new opportunities for human-agent teaming, immersive training, and the exploration of innovative tactics in defense contexts. |
| title | Towards Human Engagement with Realistic AI Combat Pilots |
| topic | Artificial Intelligence Human-Computer Interaction Machine Learning Multiagent Systems Robotics |
| url | https://arxiv.org/abs/2509.26002 |