76 citations · 308 across the 72 of their papers we have counts for
8 papers · 1 filter
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…
Network Preference Dynamics using Lattice Theory
Hans Riess, Gregory Henselman-Petrusek, Michael C. Munger +3
Preferences, fundamental in all forms of strategic behavior and collective decision-making, in their raw form, are an abstract ordering on a set of alternatives. Agents, we assume,…
Policy Stitching: Learning Transferable Robot Policies
Pingcheng Jian, Easop Lee, Zachary Bell +2
Training robots with reinforcement learning (RL) typically involves heavy interactions with the environment, and the acquired skills are often sensitive to changes in task environm…
Wasserstein Distributionally Robust Policy Evaluation and Learning for Contextual Bandits
Yi Shen, Pan Xu, Michael M. Zavlanos
Off-policy evaluation and learning are concerned with assessing a given policy and learning an optimal policy from offline data without direct interaction with the environment. Oft…
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…
Max-Plus Synchronization in Decentralized Trading Systems
Hans Riess, Michael Munger, Michael M. Zavlanos
We introduce a decentralized mechanism for pricing and exchanging alternatives constrained by transaction costs. We characterize the time-invariant solutions of a heat equation inv…
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…