2 citations · 4 across the 18 of their papers we have counts for
10 papers · 1 filter
ExactVariance of Random Return in Distributional LQR and Its Application to Mean-Variance Optimal Control
Ruyi Teng, Zifan Wang, Yulong Gao
The classical linear quadratic regulator (LQR) minimizes the expected cumulative return but fails to account for performance variability, rendering it inadequate for risk-aware app…
Wasserstein Distributionally Robust Nash Equilibrium Seeking with Heterogeneous Data: A Lagrangian Approach
Zifan Wang, Georgios Pantazis, Sergio Grammatico +2
We study a class of distributionally robust games where agents are allowed to heterogeneously choose their risk aversion with respect to distributional shifts of the uncertainty. I…
First- and Zeroth-Order Learning in Asynchronous Games
Zifan Wang, Xinlei Yi, Michael M. Zavlanos +1
This paper investigates the discrete-time asynchronous games in which noncooperative agents seek to minimize their individual cost functions. Building on the assumption of partial…
Projected Gradient Descent for Constrained Decision-Dependent Optimization
Zifan Wang, Changxin Liu, Thomas Parisini +2
This paper considers the decision-dependent optimization problem, where the data distributions react in response to decisions affecting both the objective function and linear const…
Learning of Nash Equilibria in Risk-Averse Games
Zifan Wang, Yi Shen, Michael M. Zavlanos +1
This paper considers risk-averse learning in convex games involving multiple agents that aim to minimize their individual risk of incurring significantly high costs. Specifically,…
Policy Evaluation in Distributional LQR (Extended Version)
Zifan Wang, Yulong Gao, Siyi Wang +3
Distributional reinforcement learning (DRL) enhances the understanding of the effects of the randomness in the environment by letting agents learn the distribution of a random retu…
Constrained Optimization with Decision-Dependent Distributions
Zifan Wang, Changxin Liu, Thomas Parisini +2
In this paper we deal with stochastic optimization problems where the data distributions change in response to the decision variables. Traditionally, the study of optimization prob…
Convergence Analysis of the Best Response Algorithm for Time-Varying Games
Zifan Wang, Yi Shen, Michael M. Zavlanos +1
This paper studies a class of strongly monotone games involving non-cooperative agents that optimize their own time-varying cost functions. We assume that the agents can observe ot…
Asymmetric Feedback Learning in Online Convex Games
Zifan Wang, Xinlei Yi, Yi Shen +2
This paper considers convex games involving multiple agents that aim to minimize their own cost functions using locally available information. A common assumption in the study of s…
Policy Evaluation in Distributional LQR
Zifan Wang, Yulong Gao, Siyi Wang +3
Distributional reinforcement learning (DRL) enhances the understanding of the effects of the randomness in the environment by letting agents learn the distribution of a random retu…