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We introduce a new model of combinatorial contracts in which a principal delegates the execution of a costly task to an agent. To complete the task, the agent can take any subset of a given set of unobservable actions, each of which has an…

Computer Science and Game Theory · Computer Science 2025-09-03 Paul Duetting , Tomer Ezra , Michal Feldman , Thomas Kesselheim

We propose an enhancement to wholesale electricity markets whereby the exposure of consumers to increasingly large and volatile consumer payments arising as a byproduct of volatile real-time net loads -- i.e., loads minus renewable outputs…

Optimization and Control · Mathematics 2024-08-13 Daniel Bienstock , Yury Dvorkin , Cheng Guo , Robert Mieth , Jiayi Wang

In this paper we consider a principal agent problem where the agent is allowed to quit, by incurring a cost. When the current agent quits the job, the principal will hire a new one, possibly with a different type. We characterize the…

Optimization and Control · Mathematics 2024-09-04 Jianfeng Zhang , Zimu Zhu

In the classical principal-agent problem, a principal must design a contract to incentivize an agent to perform an action on behalf of the principal. We study the classical principal-agent problem in a setting where the agent can be of one…

Computer Science and Game Theory · Computer Science 2020-10-15 Guru Guruganesh , Jon Schneider , Joshua Wang

This paper presents a new theory, known as robust dynamic pro- gramming, for a class of continuous-time dynamical systems. Different from traditional dynamic programming (DP) methods, this new theory serves as a fundamental tool to analyze…

Optimization and Control · Mathematics 2018-09-18 Tao Bian , Zhong-Ping Jiang

The recent work by Cvitani\'c, Possama\"i, and Touzi (2018) [9] presents a general approach for continuous-time principal-agent problems, through dynamic programming and second-order backward stochastic differential equations (BSDEs). In…

Optimization and Control · Mathematics 2025-06-16 Alessandro Chiusolo , Emma Hubert

The rapid growth of weather-dependent renewable generation increases price volatility and imbalance penalty risk in power markets, creating the need for advanced quantitative trading strategies. We develop a data-driven continuous-time…

Mathematical Finance · Quantitative Finance 2026-05-01 Chiheb Ben Hammouda , Michael Samet , Raúl Tempone

We address a dynamic pricing problem for airlines aiming to maximize expected revenue from selling cargo space on a single-leg flight. The cargo shipments' weight and volume are uncertain and their precise values remain unavailable at the…

Optimization and Control · Mathematics 2024-04-09 Chengyu Du , Fang He , Xi Lin

The agency problem emerges in today's large scale machine learning tasks, where the learners are unable to direct content creation or enforce data collection. In this work, we propose a theoretical framework for aligning economic interests…

Machine Learning · Computer Science 2024-07-03 Jibang Wu , Siyu Chen , Mengdi Wang , Huazheng Wang , Haifeng Xu

This work proposes a novel risk-perception-aware (RPA) control design using non-rational perception of risks associated with uncertain dynamic spatial costs. We use Cumulative Prospect Theory (CPT) to model the risk perception of a decision…

Systems and Control · Electrical Eng. & Systems 2021-09-13 Aamodh Suresh , Sonia Martinez

We study hidden-action principal-agent problems in which a principal commits to an outcome-dependent payment scheme (called contract) so as to incentivize the agent to take a costly, unobservable action leading to favorable outcomes. In…

Computer Science and Game Theory · Computer Science 2022-08-18 Matteo Castiglioni , Alberto Marchesi , Nicola Gatti

I analyze long-term contracting in insurance markets with asymmetric information. The buyer privately observes her risk type, which evolves stochastically over time. A long-term contract specifies a menu of insurance policies, contingent on…

Theoretical Economics · Economics 2022-09-01 Vitor Farinha Luz

The increasing penetration of renewable energy has introduced substantial volatility into wholesale electricity markets, complicating the optimal bidding strategies for power producers. Traditional Reinforcement Learning (RL) approaches…

Multiagent Systems · Computer Science 2026-05-06 Jiayi Chen , Xuan Zhang , Guiling Wang

Demand response (DR) refers to change in electricity consumption pattern of customers during on-peak hours in lieu of financial gains to reduce stress on distribution systems. Existing dynamic price models have not provided adequate success…

Systems and Control · Electrical Eng. & Systems 2021-05-24 Rayees A. Thokar , Nikhil Gupta , K. R. Niazi , Anil Swarnkar , Nand K. Meena

The Contract Net Protocol (1980) introduced coordination through contracts in multi-agent systems. Modern agent protocols standardize connectivity and interoperability; yet, none provide formal, resource governance-normative mechanisms to…

Multiagent Systems · Computer Science 2026-03-26 Qing Ye , Jing Tan

A runtime assurance system (RTA) for a given plant enables the exercise of an untrusted or experimental controller while assuring safety with a backup (or safety) controller. The relevant computational design problem is to create a logic…

Systems and Control · Electrical Eng. & Systems 2023-10-09 Kristina Miller , Christopher K. Zeitler , William Shen , Kerianne Hobbs , Sayan Mitra , John Schierman , Mahesh Viswanathan

We use martingale and stochastic analysis techniques to study a continuous-time optimal stopping problem, in which the decision maker uses a dynamic convex risk measure to evaluate future rewards. We also find a saddle point for an…

Probability · Mathematics 2009-11-23 Erhan Bayraktar , Ioannis Karatzas , Song Yao

The problem of order execution is cast as a relative entropy-regularized robust optimal control problem in this article. The order execution agent's goal is to maximize an objective functional associated with his profit-and-loss of trading…

Optimization and Control · Mathematics 2024-09-11 Meng Wang , Tai-Ho Wang

We study a bilevel \emph{max-max} optimization framework for principal-agent contract design, in which a principal chooses incentives to maximize utility while anticipating the agent's best response. This problem, central to moral hazard…

Machine Learning · Computer Science 2025-10-27 Tomer Galanti , Aarya Bookseller , Korok Ray

In the combinatorial action model of contract design, a principal delegates a complex project to an agent, incentivizing a subset of actions from a ground set of $n$ actions, via a linear contract. Computing the optimal contract is a…

Computer Science and Game Theory · Computer Science 2026-04-17 Elizabeth Baldwin , Paul Duetting , Michal Feldman , Maya Schlesinger
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