6 papers
When Do Institutions Beat Intelligence?
Zhengye Han
More capable agents do not necessarily form a more capable collective. A multi-agent system may jointly possess sufficient information yet fail because evidence is poorly routed, u…
RCSP: Risk-Sensitive Conjectural Scenario Planning for Safe Dynamic Robot Navigation
Zhengye Han, Quanyan Zhu
Mobile robots can fail before they collide: a velocity that is safe now may commit the robot to a passage that moving obstacles will soon close. We study this predictive near-miss…
Performative Scenario Optimization
Quanyan Zhu, Zhengye Han
This paper introduces a performative scenario optimization framework for decision-dependent chance-constrained problems. Unlike classical stochastic optimization, we account for th…
Learning, Misspecification, and Cognitive Arbitrage in Linear-Quadratic Network Games
Quanyan Zhu, Zhengye Han
We study strategic interaction in linear-quadratic network games where agents act on subjective, misspecified models of their environment. Agents observe noisy aggregate signals ge…
Split-Merge Dynamics for Shapley-Fair Coalition Formation
Quanyan Zhu, Zhengye Han
Coalition formation is often modeled as a static equilibrium problem, neglecting the dynamic processes governing how agents self-organize. This paper proposes a dynamic split-and-m…
A Mathematical Programming Approach to Computing and Learning Berk--Nash Equilibria in Infinite-Horizon MDPs
Quanyan Zhu, Zhengye Han
We study sequential decision-making when the agent's internal model class is misspecified. Within the infinite-horizon Berk-Nash framework, stable behavior arises as a fixed point:…