3 citations · 10 across the 13 of their papers we have counts for
6 papers · 1 filter
Towards AI-Assisted Generation of Military Training Scenarios
Soham Hans, Volkan Ustun, Benjamin Nye +2
Achieving expert-level performance in simulation-based training relies on the creation of complex, adaptable scenarios, a traditionally laborious and resource intensive process. Al…
X-Ego: Acquiring Team-Level Tactical Situational Awareness via Cross-Egocentric Contrastive Video Representation Learning
Yunzhe Wang, Soham Hans, Volkan Ustun
Human team tactics emerge from each player's individual perspective and their ability to anticipate, interpret, and adapt to teammates' intentions. While advances in video understa…
Implicit Behavioral Alignment of Language Agents in High-Stakes Crowd Simulations
Yunzhe Wang, Gale M. Lucas, Burcin Becerik-Gerber +1
Language-driven generative agents have enabled large-scale social simulations with transformative uses, from interpersonal training to aiding global policy-making. However, recent…
A Data-Driven Discretized CS:GO Simulation Environment to Facilitate Strategic Multi-Agent Planning Research
Yunzhe Wang, Volkan Ustun, Chris McGroarty
Modern simulation environments for complex multi-agent interactions must balance high-fidelity detail with computational efficiency. We present DECOY, a novel multi-agent simulator…
Detecting AI Assistance in Abstract Complex Tasks
Tyler King, Nikolos Gurney, John H. Miller +1
Detecting assistance from artificial intelligence is increasingly important as they become ubiquitous across complex tasks such as text generation, medical diagnosis, and autonomou…
Abstracting Geo-specific Terrains to Scale Up Reinforcement Learning
Volkan Ustun, Soham Hans, Rajay Kumar +1
Multi-agent reinforcement learning (MARL) is increasingly ubiquitous in training dynamic and adaptive synthetic characters for interactive simulations on geo-specific terrains. Fra…