activity
20242026
collaborators

12 papers

cs.RO2026

Strategizing at Speed: A Learned Model Predictive Game for Multi-Agent Drone Racing

Andrei-Carlo Papuc, Lasse Peters, Sihao Sun +2

Autonomous drone racing pushes the boundaries of high-speed motion planning and multi-agent strategic decision-making. Success in this domain requires drones not only to navigate a…

cs.RO2026

Coordinated Diffusion: Generating Multi-Agent Behavior Without Multi-Agent Demonstrations

Lasse Peters, Laura Ferranti, Andrea Bajcsy +1

Imitation learning powered by generative models has proven effective for modeling complex single-agent behaviors. However, teaching multi-agent systems, like multiple arms or vehic…

cs.LG2026

Controllability in preference-conditioned multi-objective reinforcement learning

Pau de las Heras Molins, Beyazit Yalcinkaya, Lasse Peters +2

Multi-objective reinforcement learning (MORL) allows a user to express preference over outcomes in terms of the relative importance of the objectives, but standard metrics cannot c…

eess.SY2026

Homotopy-Guided Potential Games for Congestion-Aware Navigation

Mohammed Irshadh Ismaaeel Sathyamangalam Imran, Lasse Peters, Michael Khayyat +3

We address the multi-agent motion planning problem where interactions, collisions, and congestion co-exist. Conventional game-theoretic planners capture interactions among agents b…

cs.GT2026

Breaking Exponential Complexity in Games of Ordered Preference: A Tractable Reformulation

Dong Ho Lee, Jingqi Li, Lasse Peters +2

Games of ordered preference (GOOPs) model multi-player equilibrium problems in which each player maintains a distinct hierarchy of strictly prioritized objectives. Existing approac…

cs.LG2026

Bayesian Inverse Games with High-Dimensional Multi-Modal Observations

Yash Jain, Xinjie Liu, Lasse Peters +2

Many multi-agent interaction scenarios can be naturally modeled as noncooperative games, where each agent's decisions depend on others' future actions. However, deploying game-theo…