5 papers
DNQ: Deep Nash Q-Network for Partially Observable n-Player Games
Qintong Xie, Edward Koh, Xavier Cadet +1
Many real-world competitive systems require multiple decision-makers to act simultaneously under shared constraints, limited information, and repeated interaction, as in auctions,…
FORMULA: FORmation MPC with neUral barrier Learning for safety Assurance
Qintong Xie, Weishu Zhan, Peter Chin
Multi-robot systems (MRS) are essential for large-scale applications such as disaster response, material transport, and warehouse logistics, yet ensuring robust, safety-aware forma…
Nash Q-Network for Multi-Agent Cybersecurity Simulation
Qintong Xie, Edward Koh, Xavier Cadet +1
Cybersecurity defense involves interactions between adversarial parties (namely defenders and hackers), making multi-agent reinforcement learning (MARL) an ideal approach for model…
Explore Reinforced: Equilibrium Approximation with Reinforcement Learning
Ryan Yu, Mateusz Nowak, Qintong Xie +2
Current approximate Coarse Correlated Equilibria (CCE) algorithms struggle with equilibrium approximation for games in large stochastic environments but are theoretically guarantee…
Preprocessing-based Kinodynamic Motion Planning Framework for Intercepting Projectiles using a Robot Manipulator
Ramkumar Natarajan, Hanlan Yang, Qintong Xie +6
We are interested in studying sports with robots and starting with the problem of intercepting a projectile moving toward a robot manipulator equipped with a shield. To successfull…