WIP: Human-AI interactions in real-world complex environments using a comprehensive reinforcement learning framework

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AAMAS, the International Conference on Autonomous Agents and Multiagent Systems, is a premier event in the field of artificial intelligence that focuses on both the theoretical and practical aspects of autonomous agents and multi-agent systems.

This paper is the result of a collaboration between AIR, Thales, the University of Alberta and JACOBB.ai.

The paper discusses the use of a novel multi-agent simulator for defense applications, based on Cogment, integrating human and AI capabilities to protect critical infrastructure like airports. By incorporating human feedback and demonstrations into the training of AI agents, the system leverages both human expertise and AI efficiency to enhance decision-making and response strategies in complex, dynamic scenarios. This approach not only improves the learning process and operational performance of AI agents but also maintains meaningful human control over critical tasks.

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@inproceedings{humanaiinteractions2023,
  title={
    {WIP}: Human-AI interactions in real-world complex environments using a comprehensive reinforcement learning framework
  },
  author={
    Islam, Md Saiful and
    Das, Srijita and
    Gottipati, Sai Krishna and
    Duguay, William and
    Mars, Clodéric and
    Arabneydi, Jalal and
    Fagette, Antoine and
    Guzdial, Matthew and
    Taylor, Matthew E.
  },
  booktitle={Adaptive Learning Agents Workshop, ALA 2023, Held as Part of the AAMAS 2023},
  year={2023}
}