6 papers
Multi-agent Reach-avoid MDP via Potential Games and Low-rank Policy Structure
Adam Casselman, Abraham P. Vinod, Sarah H. Q. Li
We optimize finite horizon multi-agent reach-avoid Markov decision process (MDP) via \emph{local feedback policies}. The global feedback policy solution yields global optimality bu…
When the Correct Model Fails: The Optimality of Stackelberg Equilibria with Follower Intention Updates
Cayetana Salinas-Rodriguez, Jonathan Rogers, Sarah H. Q. Li
We study a two-player dynamic Stackelberg game where the follower's intention is unknown to the leader. Classical formulations of the Stackelberg equilibrium (SE) assume that the f…
Distributionally Robust Tolls for Traffic Networks with Affine Latency Functions
Chih-Yuan Chiu, Sarah H. Q. Li, Bryce L. Ferguson
In network congestion games, system operators often utilize latency models, estimated from real-world traffic flow and travel time data, to design monetary incentives which steer e…
Language Conditioning Improves Accuracy of Aircraft Goal Prediction in Non-Towered Airspace
Sundhar Vinodh Sangeetha, Chih-Yuan Chiu, Sarah H. Q. Li +1
Autonomous aircraft must safely operate in non-towered airspace, where coordination relies on voice-based communication among human pilots. Safe operation requires an aircraft to p…
Allocating Corrective Control to Mitigate Multi-agent Safety Violations Under Private Preferences
Johnathan Corbin, Sarah H. Q. Li, Jonathan Rogers
We propose a novel framework that computes the corrective control efforts to ensure joint safety in multi-agent dynamical systems. This framework efficiently distributes the requir…
Computing Optimal Joint Chance Constrained Control Policies
Niklas Schmid, Marta Fochesato, Sarah H. Q. Li +2
We consider the problem of optimally controlling stochastic, Markovian systems subject to joint chance constraints over a finite-time horizon. For such problems, standard Dynamic P…