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Related papers: Stackelberg Risk Preference Design

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This paper provides a systematic study of the robust Stackelberg equilibrium (RSE), which naturally generalizes the widely adopted solution concept of the strong Stackelberg equilibrium (SSE). The RSE accounts for any possible…

Computer Science and Game Theory · Computer Science 2025-06-03 Jiarui Gan , Minbiao Han , Jibang Wu , Haifeng Xu

We study a two-player dynamic Stackelberg game where the follower's intention is unknown to the leader. Classical formulations of the Stackelberg equilibrium (SE) assume that the follower's best response (BR) function is known to the…

Systems and Control · Electrical Eng. & Systems 2026-04-09 Cayetana Salinas-Rodriguez , Jonathan Rogers , Sarah H. Q. Li

This paper addresses a Stackelberg stochastic linear-quadratic (LQ) differential game under closed-loop information, a problem inherently time-inconsistent. Existing approaches rely on solving two coupled Hamilton-Jacobi-Bellman (HJB)…

Optimization and Control · Mathematics 2026-04-27 Qi Lü , Bowen Ma , Hanxiao Wang

This paper investigates a hybrid stochastic differential reinsurance and investment game between one reinsurer and two insurers, including a stochastic Stackelberg differential subgame and a non-zero-sum stochastic differential subgame. The…

Mathematical Finance · Quantitative Finance 2019-10-23 Yanfei Bai , Zhongbao Zhou , Helu Xiao , Rui Gao , Feimin Zhong

This paper is concerned with a leader-follower stochastic differential game with asymmetric information, where the information available to the follower is based on some sub-$\sigma$-algebra of that available to the leader. Such kind of…

Optimization and Control · Mathematics 2015-09-15 Jingtao Shi , Guangchen Wang , Jie Xiong

The sequential recommendation task aims to predict the item that user is interested in according to his/her historical action sequence. However, inevitable random action, i.e. user randomly accesses an item among multiple candidates or…

Information Retrieval · Computer Science 2024-04-09 Sirui Wang , Peiguang Li , Yunsen Xian , Hongzhi Zhang

Machine learning systems have been widely used to make decisions about individuals who may behave strategically to receive favorable outcomes, e.g., they may genuinely improve the true labels or manipulate observable features directly to…

Artificial Intelligence · Computer Science 2024-10-30 Tian Xie , Zhiqun Zuo , Mohammad Mahdi Khalili , Xueru Zhang

Strategic information disclosure, in its simplest form, considers a game between an information provider (sender) who has access to some private information that an information receiver is interested in. While the receiver takes an action…

Computer Science and Game Theory · Computer Science 2024-03-14 Raj Kiriti Velicheti , Melih Bastopcu , S. Rasoul Etesami , Tamer Başar

This paper studies continuous-time optimal contracting in a hierarchy problem which generalises the model of Sung (2015). The hierarchy is modeled by a series of interlinked principal-agent problems, leading to a sequence of Stackelberg…

Optimization and Control · Mathematics 2020-07-22 Emma Hubert

In this paper, we first consider a pinning node selection and control gain co-design problem for complex networks. A necessary and sufficient condition for the synchronization of the pinning controlled networks at a homogeneous state is…

Systems and Control · Electrical Eng. & Systems 2019-09-04 Yuzhe Li , Dawei Shi , Tongwen Chen

Risk-sensitive planning aims to identify policies maximizing some tail-focused metrics in Markov Decision Processes (MDPs). Such an optimization task can be very costly for the most widely used and interpretable metrics such as threshold…

Machine Learning · Statistics 2025-07-09 Alexandre Marthe , Samuel Bounan , Aurélien Garivier , Claire Vernade

We introduce the application of online learning in a Stackelberg game pertaining to a system with two learning agents in a dyadic exchange network, consisting of a supplier and retailer, specifically where the parameters of the demand…

Computational Engineering, Finance, and Science · Computer Science 2024-10-15 Larkin Liu , Yuming Rong

In this paper, we consider a risk-averse decision problem for controlled-diffusion processes, with dynamic risk measures, in which there are two risk-averse decision makers (i.e., {\it leader} and {\it follower}) with different risk-averse…

Optimization and Control · Mathematics 2016-10-25 Getachew K. Befekadu , Eduardo L. Pasiliao

Stackelberg Pricing Games is a two-level combinatorial pricing problem studied in the Economics, Operation Research, and Computer Science communities. In this paper, we consider the decade-old shortest path version of this problem which is…

Computer Science and Game Theory · Computer Science 2009-10-05 Parinya Chalermsook , Bundit Laekhanukit , Danupon Nanongkai

This paper is concerned with the stochastic linear quadratic Stackelberg differential game with overlapping information, where the diffusion terms contain the control and state variables. Here the term "overlapping" means that there are…

Optimization and Control · Mathematics 2018-05-01 Jingtao Shi , Guangchen Wang , Jie Xiong

Principal-agent problems arise when one party acts on behalf of another, leading to conflicts of interest. The economic literature has extensively studied principal-agent problems, and recent work has extended this to more complex scenarios…

Artificial Intelligence · Computer Science 2024-01-02 Omer Ben-Porat , Yishay Mansour , Michal Moshkovitz , Boaz Taitler

In multi-agent problems requiring a high degree of cooperation, success often depends on the ability of the agents to adapt to each other's behavior. A natural solution concept in such settings is the Stackelberg equilibrium, in which the…

Machine Learning · Computer Science 2024-06-14 Robert Loftin , Mustafa Mert Çelikok , Herke van Hoof , Samuel Kaski , Frans A. Oliehoek

This paper investigates a linear quadratic mean field leader-follower team problem, where the model involves one leader and a large number of weakly-coupled interactive followers. The leader and the followers cooperate to optimize the…

Optimization and Control · Mathematics 2020-08-13 Jianhui Huang , Bing-Chang Wang , Tinghan Xie

We propose a generalization of the Bass diffusion model in discrete-time that explicitly models the effect of price in adoption. Our model is different from earlier price-incorporated models and fits well to adoption data for various…

Systems and Control · Electrical Eng. & Systems 2025-12-04 Yijin Wang , Subhonmesh Bose

We address the problem of making a pre-trained reinforcement learning (RL) policy safety-aware by incorporating cost constraints without retraining it from scratch. While costs could be numerically encoded, we assume a more general setting…

Machine Learning · Computer Science 2026-05-21 Richa Verma , Bavish Kulur , Sanjay Chawla , Balaraman Ravindran
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