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Related papers: Commitment with Signaling under Double-sided Infor…

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Agents rarely act in isolation -- their behavioral history, in particular, is public to others. We seek a non-asymptotic understanding of how a leader agent should shape this history to its maximal advantage, knowing that follower agent(s)…

Computer Science and Game Theory · Computer Science 2019-05-29 Vidya Muthukumar , Anant Sahai

Algorithms for playing in Stackelberg games have been deployed in real-world domains including airport security, anti-poaching efforts, and cyber-crime prevention. However, these algorithms often fail to take into consideration the…

Computer Science and Game Theory · Computer Science 2024-10-15 Keegan Harris , Zhiwei Steven Wu , Maria-Florina Balcan

We study a continuous-time stochastic Stackelberg game in which a leader seeks to accomplish a primary objective while inferring a hidden parameter of a rational follower. The follower solves an entropy-regularized tracking problem and…

Optimization and Control · Mathematics 2025-10-08 Ruimeng Hu , Daniel Ralston , Xu Yang , Haosheng Zhou

The commitment power of senders distinguishes Bayesian persuasion problems from other games with (strategic) communication. Persuasion games with multiple senders have largely studied simultaneous commitment and signalling settings.…

Theoretical Economics · Economics 2022-02-15 Shih-Tang Su , Vijay G. Subramanian

Many decentralized and networked control problems involve decision makers which have either misaligned criteria or subjective priors. In the context of such a setup, in this paper we consider binary signaling problems in which the decision…

Optimization and Control · Mathematics 2019-09-06 Serkan Sarıtaş , Sinan Gezici , Serdar Yüksel

Game-theoretic inverse learning is the problem of inferring a player's objectives from their actions. We formulate an inverse learning problem in a Stackelberg game between a leader and a follower, where each player's action is the…

Computer Science and Game Theory · Computer Science 2024-10-15 William Ward , Yue Yu , Jacob Levy , Negar Mehr , David Fridovich-Keil , Ufuk Topcu

In 1996, Mallozzi and Morgan [33] proposed a new model for Stackelberg games which we refer here to as the Bayesian approach. The leader has only partial information about how followers select their reaction among possibly multiple optimal…

Optimization and Control · Mathematics 2023-05-12 David Salas , Anton Svensson

Two-player zero-sum repeated games are well understood. Computing the value of such a game is straightforward. Additionally, if the payoffs are dependent on a random state of the game known to one, both, or neither of the players, the…

Information Theory · Computer Science 2009-11-05 Paul Cuff

This study investigates the relationship between resilience of control systems to attacks and the information available to malicious attackers. Specifically, it is shown that control systems are guaranteed to be secure in an asymptotic…

Systems and Control · Electrical Eng. & Systems 2020-03-27 Hampei Sasahara , Serkan Saritas , Henrik Sandberg

This work investigates a dynamic variant of Bayesian persuasion, in which a strategic sender seeks to influence a receiver's belief over time through controlling the timing of the information disclosure, under resource constraints. We…

Information Theory · Computer Science 2025-12-05 Ahmet Bugra Gundogan , Melih Bastopcu

We extend the formalism of Conjectural Variations games to Stackelberg games involving multiple leaders and a single follower. To solve these nonconvex games, a common assumption is that the leaders compute their strategies having perfect…

Computer Science and Game Theory · Computer Science 2025-07-24 Francesco Morri , Hélène Le Cadre , Luce Brotcorne

A Stackelberg game is played between a leader and a follower. The leader first chooses an action, then the follower plays his best response. The goal of the leader is to pick the action that will maximize his payoff given the follower's…

Data Structures and Algorithms · Computer Science 2015-11-19 Aaron Roth , Jonathan Ullman , Zhiwei Steven Wu

There has been a recent surge of interest in the role of information in strategic interactions. Much of this work seeks to understand how the realized equilibrium of a game is influenced by uncertainty in the environment and the information…

Computer Science and Game Theory · Computer Science 2014-07-22 Shaddin Dughmi

Recent results in the ML community have revealed that learning algorithms used to compute the optimal strategy for the leader to commit to in a Stackelberg game, are susceptible to manipulation by the follower. Such a learning algorithm…

Computer Science and Game Theory · Computer Science 2022-09-12 Georgios Birmpas , Jiarui Gan , Alexandros Hollender , Francisco J. Marmolejo-Cossío , Ninad Rajgopal , Alexandros A. Voudouris

We study online learning in Bayesian Stackelberg games, where a leader repeatedly interacts with a follower whose unknown private type is independently drawn at each round from an unknown probability distribution. The goal is to design…

Computer Science and Game Theory · Computer Science 2026-02-03 Matteo Bollini , Francesco Bacchiocchi , Samuel Coutts , Matteo Castiglioni , Alberto Marchesi

We study the value and the optimal strategies for a two-player zero-sum optimal stopping game with incomplete and asymmetric information. In our Bayesian set-up, the drift of the underlying diffusion process is unknown to one player…

Probability · Mathematics 2020-07-15 Tiziano De Angelis , Erik Ekström , Kristoffer Glover

In this paper, we present a conceptual model game to examine the dynamics of asymmetric interactions in games with imperfect information. The game involves two agents with starkly contrasting capabilities: one agent can take actions but has…

Multiagent Systems · Computer Science 2025-01-09 Fabian Farestam , Dilian Gurov

Leadership games provide a powerful paradigm to model many real-world settings. Most literature focuses on games with a single follower who acts optimistically, breaking ties in favour of the leader. Unfortunately, for real-world…

Artificial Intelligence · Computer Science 2018-08-01 Giuseppe De Nittis , Alberto Marchesi , Nicola Gatti

When interacting with other decision-making agents in non-adversarial scenarios, it is critical for an autonomous agent to have inferable behavior: The agent's actions must convey their intention and strategy. We model the inferability…

Computer Science and Game Theory · Computer Science 2025-06-03 Mustafa O. Karabag , Sophia Smith , Negar Mehr , David Fridovich-Keil , Ufuk Topcu

A persuasion policy successfully persuades an agent to pick a particular action only if the information is designed in a manner that convinces the agent that it is in their best interest to pick that action. Thus, it is natural to ask, what…

Computer Science and Game Theory · Computer Science 2024-08-27 Reema Deori , Ankur A. Kulkarni