3 citations · 3 across the 5 of their papers we have counts for
5 papers
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…
Zero-sum turn games using Q-learning: finite computation with security guarantees
Sean Anderson, Chris Darken, João Hespanha
This paper addresses zero-sum ``turn'' games, in which only one player can make decisions at each state. We show that pure saddle-point state-feedback policies for turn games can b…
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…
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…
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…