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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

In competitive resource allocation formulations multiple agents compete over different contests by committing their limited resources in them. For these settings, contest games offer a game-theoretic foundation to analyze how players can…

Computer Science and Game Theory · Computer Science 2024-08-05 Gilberto Diaz-Garcia , Francesco Bullo , Jason R. Marden

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

We study the computational complexity of finding Stackelberg Equilibria in general-sum games, where the set of pure strategies of the leader and the followers are exponentially large in a natrual representation of the problem. In…

Computer Science and Game Theory · Computer Science 2019-09-10 Avrim Blum , Nika Hagtalab , MohammadTaghi Hajiaghayi , Saeed Seddighin

This paper studies a class of dynamic Stackelberg games under open-loop information structure with constrained linear agent dynamics and quadratic utility functions. We show two important properties for this class of dynamic Stackelberg…

Optimization and Control · Mathematics 2016-08-09 Sen Li , Wei Zhang , Jianming Lian , Karanjit Kalsi

We introduce a reinforcement learning framework for economic design where the interaction between the environment designer and the participants is modeled as a Stackelberg game. In this game, the designer (leader) sets up the rules of the…

Computer Science and Game Theory · Computer Science 2024-07-22 Gianluca Brero , Alon Eden , Darshan Chakrabarti , Matthias Gerstgrasser , Amy Greenwald , Vincent Li , David C. Parkes

We study incentive designs for a class of stochastic Stackelberg games with one leader and a large number of (finite as well as infinite population of) followers. We investigate whether the leader can craft a strategy under a dynamic…

Computer Science and Game Theory · Computer Science 2024-02-13 Sina Sanjari , Subhonmesh Bose , Tamer Başar

High performance machine learning models have become highly dependent on the availability of large quantity and quality of training data. To achieve this, various central agencies such as the government have suggested for different data…

Machine Learning · Computer Science 2019-11-27 Zhiliang Chen

We study the framework of two-player Stackelberg games played on graphs in which Player 0 announces a strategy and Player 1 responds rationally with a strategy that is an optimal response. While it is usually assumed that Player 1 has a…

Computer Science and Game Theory · Computer Science 2022-03-03 Véronique Bruyère , Baptiste Fievet , Jean-François Raskin , Clément Tamines

We present a Stackelberg game model to investigate how individuals make their decisions on timing and route selection. Group formation can naturally result from these decisions, but only when individuals arrive at the same time and choose…

Computer Science and Game Theory · Computer Science 2025-08-26 Chenlan Wang , Mingyan Liu

In increasingly different contexts, it happens that a human player has to interact with artificial players who make decisions following decision-making algorithms. How should the human player play against these algorithms to maximize his…

Computer Science and Game Theory · Computer Science 2022-02-22 Maurizio D 'Andrea

We study a multi-player one-round game termed Stackelberg Network Pricing Game, in which a leader can set prices for a subset of $m$ priceable edges in a graph. The other edges have a fixed cost. Based on the leader's decision one or more…

Data Structures and Algorithms · Computer Science 2008-02-21 Patrick Briest , Martin Hoefer , Piotr Krysta

Admissibility has been studied for games of infinite duration with Boolean objectives. We extend here this study to games of infinite duration with quantitative objectives. First, we show that, un- der the assumption that optimal worst-case…

Logic in Computer Science · Computer Science 2016-11-29 Romain Brenguier , Guillermo A. Pérez , Jean-François Raskin , Ocan Sankur

The conditional commitment abilities of mutually transparent computer agents have been studied in previous work on commitment games and program equilibrium. This literature has shown how these abilities can help resolve Prisoner's Dilemmas…

Computer Science and Game Theory · Computer Science 2022-12-06 Anthony DiGiovanni , Jesse Clifton

This paper characterizes optimal classification when individuals adjust their behavior in response to the classification rule. We model the interaction between a designer and a population as a Stackelberg game: the designer selects a…

Computer Science and Game Theory · Computer Science 2026-01-16 Elizabeth Maggie Penn , John W. Patty

Commitments play a crucial role in game theory, shaping strategic interactions by either altering a player's own payoffs or influencing the incentives of others through outcome-contingent payments. While most research has focused on using…

Computer Science and Game Theory · Computer Science 2025-07-30 Maria Alejandra Ramirez , Rosemarie Nagel , David Wolpert , Jürgen Jost

The Bayesian persuasion paradigm of strategic communication models interaction between a privately-informed agent, called the sender, and an ignorant but rational agent, called the receiver. The goal is typically to design a (near-)optimal…

Computer Science and Game Theory · Computer Science 2021-06-21 Ronen Gradwohl , Niklas Hahn , Martin Hoefer , Rann Smorodinsky

We study an information-structure design problem (a.k.a. persuasion) with a single sender and multiple receivers with actions of a priori unknown types, independently drawn from action-specific marginal distributions. As in the standard…

Artificial Intelligence · Computer Science 2019-08-05 Andrea Celli , Stefano Coniglio , Nicola Gatti

This article introduces a class of $Nash$ games among $Stackelberg$ players ($NASPs$), namely, a class of simultaneous non-cooperative games where the players solve sequential Stackelberg games. Specifically, each player solves a…

Computer Science and Game Theory · Computer Science 2025-03-04 Margarida Carvalho , Gabriele Dragotto , Felipe Feijoo , Andrea Lodi , Sriram Sankaranarayanan

Optimization models have been broadly used within side the energy industry as useful decision-making systems for scheduling and dispatching electric powered energy resources; this is applied in a system called unit commitment (UC). Unit…

Optimization and Control · Mathematics 2022-04-01 Angel Zambrano
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