3 citations · 10 across the 13 of their papers we have counts for
13 papers
Indirect Geoeconomic Influence: A Switching Dynamical Systems Framework for Mechanism Design
Nikolos Gurney, Boxi Fu, Soham Hans +1
We develop a formal framework for analyzing indirect geoeconomic influence. The influencing state (sender) does not attempt to change a target nation's policy directly. Instead, th…
GameplayQA: A Benchmarking Framework for Decision-Dense POV-Synced Multi-Video Understanding of 3D Virtual Agents
Yunzhe Wang, Runhui Xu, Kexin Zheng +4
Multimodal LLMs are increasingly deployed as perceptual backbones for autonomous agents in 3D environments, from robotics to virtual worlds. These applications require agents to pe…
GraphAllocBench: A Flexible Benchmark for Preference-Conditioned Multi-Objective Policy Learning
Zhiheng Jiang, Yunzhe Wang, Ryan Marr +3
Preference-Conditioned Policy Learning (PCPL) in Multi-Objective Reinforcement Learning (MORL) approximates diverse Pareto-optimal solutions by conditioning a single policy on user…
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…
Spontaneous Theory of Mind for Artificial Intelligence
Nikolos Gurney, David V. Pynadath, Volkan Ustun
Existing approaches to Theory of Mind (ToM) in Artificial Intelligence (AI) overemphasize prompted, or cue-based, ToM, which may limit our collective ability to develop Artificial…
Controlling Synthetic Characters in Simulations: A Case for Cognitive Architectures and Sigma
Volkan Ustun, Paul S. Rosenbloom, Seyed Sajjadi +1
Simulations, along with other similar applications like virtual worlds and video games, require computational models of intelligence that generate realistic and credible behavior f…
Adaptive Synthetic Characters for Military Training
Volkan Ustun, Rajay Kumar, Adam Reilly +2
Behaviors of the synthetic characters in current military simulations are limited since they are generally generated by rule-based and reactive computational models with minimal in…
Outperforming Word2Vec on Analogy Tasks with Random Projections
Abram Demski, Volkan Ustun, Paul Rosenbloom +1
We present a distributed vector representation based on a simplification of the BEAGLE system, designed in the context of the Sigma cognitive architecture. Our method does not requ…