May 13, 2024 � This poster addresses this need by focusing on a specific scenario: training reinforcement learning agents to react to an ambush.
There is a need for realistic Opposing Forces (OPFOR) be- havior in military training simulations. Current training simulations generally only have simple, non-�...
Jul 9, 2024 � This paper presents a reinforcement learning model designed to learn how to take cover on geo-specific terrains, an essential behavior component�...
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This paper presents a reinforcement learning model designed to learn how to take cover on geo-specific terrains, an essential behavior component for military�...
Sep 10, 2024 � Training Reinforcement Learning Agents to React to an Ambush for Military Simulations. FLAIRS 2024. [c5]. view. electronic edition via DOI�...
May 16, 2024 � ... agent Reinforcement Learning (Poster). 3. Training Reinforcement Learning Agents to React to an Ambush for Military Simulations (Poster)�...
Introducing RIDE: Lowering the Barrier of Entry to Simulation and ...
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RIDE is a simulation platform that unites many Department of Defense and Army simulation efforts to provide an accelerated development foundation and�...
Finally, the U.S. Army Research Lab ported a military training scenario into the StarCraft II simulation environment and trained several RL agents.
Training Reinforcement Learning Agents to React to an Ambush for Military Simulations. FLAIRS 2024. [c25]. view. electronic edition via DOI (open access)�...
ABSTRACT: We describe an approach for dynamically generating asymmetric tactics that can drive adversary behaviors in synthetic training environments.