2 papers
cs.RO2025
A Systematic Study of Multi-Agent Deep Reinforcement Learning for Safe and Robust Autonomous Highway Ramp Entry
Larry Schester, Luis E. Ortiz
Vehicles today can drive themselves on highways and driverless robotaxis operate in major cities, with more sophisticated levels of autonomous driving expected to be available and…
cs.GT2025
A Machine Learning Approach to Detect Strategic Behavior from Large-Population Observational Data Applied to Game Mode Prediction on a Team-Based Video Game
Boshen Wang, Luis E. Ortiz
Modeling the strategic behavior of agents in a real-world multi-agent system using existing state-of-the-art computational game-theoretic tools can be a daunting task, especially w…