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We study a problem of optimal allocation in a discrete-time multi-period pure-exchange economy, where agents have preferences over stochastic endowment processes that are represented by strongly time-consistent dynamic risk measures. We…

Risk Management · Quantitative Finance 2026-03-23 Brandon Tam , Mario Ghossoub , Silvana M. Pesenti

The stable matching problem sets the economic foundation of several practical applications ranging from school choice and medical residency to ridesharing and refugee placement. It is concerned with finding a matching between two disjoint…

Computer Science and Game Theory · Computer Science 2022-02-01 Angelina Brilliantova , Hadi Hosseini

A combinatorial market consists of a set of indivisible items and a set of agents, where each agent has a valuation function that specifies for each subset of items its value for the given agent. From an optimization point of view, the goal…

Computer Science and Game Theory · Computer Science 2023-01-05 Kristóf Bérczi , Laura Codazzi , Julian Golak , Alexander Grigoriev

We consider a dynamic pricing problem for repeated contextual second-price auctions with multiple strategic buyers who aim to maximize their long-term time discounted utility. The seller has limited information on buyers' overall demand…

Machine Learning · Computer Science 2023-02-08 Negin Golrezaei , Patrick Jaillet , Jason Cheuk Nam Liang

Dynamic pricing is commonly used to regulate congestion in shared service systems. This paper is motivated by the fact that in the presence of users with varying price sensitivity (responsiveness), conventional monotonic pricing can lead to…

Systems and Control · Electrical Eng. & Systems 2026-03-24 Yingqing Chen , Anni Li , Christos G. Cassandras , Homayoun Hamedmoghadam , Fabian Wirth , Robert Shorten

We introduce the framework of performative reinforcement learning where the policy chosen by the learner affects the underlying reward and transition dynamics of the environment. Following the recent literature on performative…

Machine Learning · Computer Science 2023-06-08 Debmalya Mandal , Stelios Triantafyllou , Goran Radanovic

To regulate a social system comprised of self-interested agents, economic incentives are often required to induce a desirable outcome. This incentive design problem naturally possesses a bilevel structure, in which a designer modifies the…

Computer Science and Game Theory · Computer Science 2022-10-14 Boyi Liu , Jiayang Li , Zhuoran Yang , Hoi-To Wai , Mingyi Hong , Yu Marco Nie , Zhaoran Wang

We consider a simulation optimization problem for a context-dependent decision-making, which aims to determine the top-m designs for all contexts. Under a Bayesian framework, we formulate the optimal dynamic sampling decision as a…

Machine Learning · Statistics 2023-06-12 Gongbo Zhang , Sihua Chen , Kuihua Huang , Yijie Peng

Decision makers often aim to learn a treatment assignment policy under a capacity constraint on the number of agents that they can treat. When agents can respond strategically to such policies, competition arises, complicating estimation of…

Machine Learning · Statistics 2025-03-31 Roshni Sahoo , Stefan Wager

We consider Incentive Decision Processes, where a principal seeks to reduce its costs due to another agent's behavior, by offering incentives to the agent for alternate behavior. We focus on the case where a principal interacts with a…

Computer Science and Game Theory · Computer Science 2012-10-19 Sashank J. Reddi , Emma Brunskill

We consider a finite-horizon discrete-time dynamic system jointly controlled by a designer and one or more agents, where the designer can influence the agents' actions through selective information disclosure. At each time step, the…

Systems and Control · Electrical Eng. & Systems 2025-08-04 Renyan Sun , Ashutosh Nayyar

This paper studies an online selection problem, where a seller seeks to sequentially sell multiple copies of an item to arriving buyers. We consider an adversarial setting, making no modeling assumptions about buyers' valuations for the…

Computer Science and Game Theory · Computer Science 2024-10-11 Bo Sun , Hossein Nekouyan Jazi , Xiaoqi Tan , Raouf Boutaba

The note studies the problem of selecting a good enough subset out of a finite number of alternatives under a fixed simulation budget. Our work aims to maximize the posterior probability of correctly selecting a good subset. We formulate…

Optimization and Control · Mathematics 2023-05-09 Gongbo Zhang , Bin Chen , Qing-shan Jia , Yijie Peng

We study a sequential decision-making model where a set of items is repeatedly matched to the same set of agents over multiple rounds. The objective is to determine a sequence of matchings that either maximizes the utility of the least…

Computer Science and Game Theory · Computer Science 2025-10-07 Eugene Lim , Tzeh Yuan Neoh , Nicholas Teh

We consider the challenge of finding a deterministic policy for a Markov decision process that uniformly (in all states) maximizes one reward subject to a probabilistic constraint over a different reward. Existing solutions do not fully…

Machine Learning · Computer Science 2022-01-21 Jaeyoung Lee , Sean Sedwards , Krzysztof Czarnecki

Environments with fixed adjustment costs such as transaction costs or \lq menu costs\rq$ $ are widespread within economic systems. The presence of fixed minimal adjustment costs produces adjustment stickiness so that agents must choose a…

Optimization and Control · Mathematics 2019-10-09 David Mguni

Many decision problems in economics, information technology, and industry can be transformed to an optimal stopping of adapted random vectors with some utility function over the set of Markov times with respect to filtration build by the…

Optimization and Control · Mathematics 2020-11-04 Krzysztof Szajowski

In dynamic settings each economic agent's choices can be revealing of her private information. This elicitation via the rationalization of observable behavior depends each agent's perception of which payoff-relevant contingencies other…

Theoretical Economics · Economics 2021-05-17 Evan Piermont , Peio Zuazo-Garin

Stochastic resetting, where a dynamical process is intermittently returned to a fixed reference state, has emerged as a powerful mechanism for optimizing first-passage properties. Existing theory largely treats static, non-learning…

Machine Learning · Computer Science 2026-03-18 Jello Zhou , Vudtiwat Ngampruetikorn , David J. Schwab

Motivated by practical applications, we explore the constrained multi-period mean-variance portfolio selection problem within a market characterized by a dynamic factor model. This model captures predictability in asset returns driven by…

Portfolio Management · Quantitative Finance 2025-02-26 Jianjun Gao , Chengneng Jin , Yun Shi , Xiangyu Cui