most citedScaling Intelligent Agents in Combat Simulations for Wargaming

3 citations · 3 across the 5 of their papers we have counts for

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cs.LG2025

A Hierarchical Hybrid AI Approach: Integrating Deep Reinforcement Learning and Scripted Agents in Combat Simulations

Scotty Black, Christian Darken

In the domain of combat simulations in support of wargaming, the development of intelligent agents has predominantly been characterized by rule-based, scripted methodologies with d…

cs.LG2024

Mastering the Digital Art of War: Developing Intelligent Combat Simulation Agents for Wargaming Using Hierarchical Reinforcement Learning

Scotty Black

In today's rapidly evolving military landscape, advancing artificial intelligence (AI) in support of wargaming becomes essential. Despite reinforcement learning (RL) showing promis…

cs.LG2024

Localized Observation Abstraction Using Piecewise Linear Spatial Decay for Reinforcement Learning in Combat Simulations

Scotty Black, Christian Darken

In the domain of combat simulations, the training and deployment of deep reinforcement learning (RL) agents still face substantial challenges due to the dynamic and intricate natur…

cs.LG20243 cited

Scaling Intelligent Agents in Combat Simulations for Wargaming

Scotty Black, Christian Darken

Remaining competitive in future conflicts with technologically-advanced competitors requires us to accelerate our research and development in artificial intelligence (AI) for warga…

cs.LG2024

Scaling Artificial Intelligence for Digital Wargaming in Support of Decision-Making

Scotty Black, Christian Darken

In this unprecedented era of technology-driven transformation, it becomes more critical than ever that we aggressively invest in developing robust artificial intelligence (AI) for…