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We consider a broad class of stochastic imitation dynamics over networks, encompassing several well known learning models such as the replicator dynamics. In the considered models, players have no global information about the game…

Systems and Control · Computer Science 2021-03-02 Lorenzo Zino , Giacomo Como , Fabio Fagnani

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

The paper is devoted to inverse Stackelberg games with many players. We consider both static and differential games. The main assumption of the paper is the compactness of the strategy sets. We obtain the characterization of inverse…

Optimization and Control · Mathematics 2014-04-21 Yurii Averboukh

We investigate a stochastic differential game in which a major player has a private information (the knowledge of a random variable), which she discloses through her control to a population of small players playing in a Nash Mean Field Game…

Optimization and Control · Mathematics 2023-11-28 Philippe Bergault , Pierre Cardaliaguet , Catherine Rainer

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

Merging in the form of a mandatory lane-change is an important issue in transportation research. Even when safely completed, merging may disturb the mainline traffic and reduce the efficiency or capacity of the roadway. In this paper, we…

Computer Science and Game Theory · Computer Science 2020-03-24 Jehong Yoo , Reza Langari

Most models of Stackelberg security games assume that the attacker only knows the defender's mixed strategy, but is not able to observe (even partially) the instantiated pure strategy. Such partial observation of the deployed pure strategy…

Computer Science and Game Theory · Computer Science 2015-05-05 Haifeng Xu , Albert X. Jiang , Arunesh Sinha , Zinovi Rabinovich , Shaddin Dughmi , Milind Tambe

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

We study a two-player Stackelberg game with incomplete information such that the follower's strategy belongs to a known family of parameterized functions with an unknown parameter vector. We design an adaptive learning approach to…

Computer Science and Game Theory · Computer Science 2021-01-12 Guosong Yang , Radha Poovendran , João P. Hespanha

At the beginning of a dynamic game, players may have exogenous theories about how the opponents are going to play. Suppose that these theories are commonly known. Then, players will refine their first-order beliefs, and challenge their own…

Computer Science and Game Theory · Computer Science 2017-07-28 Emiliano Catonini

Creating incentives for cooperation is a challenge in natural and artificial systems. One potential answer is reputation, whereby agents trade the immediate cost of cooperation for the future benefits of having a good reputation. Game…

Multiagent Systems · Computer Science 2021-02-16 Nicolas Anastassacos , Julian García , Stephen Hailes , Mirco Musolesi

This contribution deals with a two-level discrete decision problem, a so-called Stackelberg strategic game: A Subset Sum setting is addressed with a set $N$ of items with given integer weights. One distinguished player, the leader, may…

Discrete Mathematics · Computer Science 2018-01-12 Ulrich Pferschy , Gaia Nicosia , Andrea Pacifici

Mutually beneficial behavior in repeated games can be enforced via the threat of punishment, as enshrined in game theory's well-known "folk theorem." There is a cost, however, to a player for generating these disincentives. In this work, we…

Human-Computer Interaction · Computer Science 2019-08-26 Matt Cooper , Jun Ki Lee , Jacob Beck , Joshua D. Fishman , Michael Gillett , Zoë Papakipos , Aaron Zhang , Jerome Ramos , Aansh Shah , Michael L. Littman

Risk measures are commonly used to capture the risk preferences of decision-makers (DMs). The decisions of DMs can be nudged or manipulated when their risk preferences are influenced by factors such as the availability of information about…

Optimization and Control · Mathematics 2023-11-29 Shutian Liu , Quanyan Zhu

We examine the problem of the existence of optimal deterministic stationary strategiesintwo-players antagonistic (zero-sum) perfect information stochastic games with finitely many states and actions.We show that the existenceof such…

Computer Science and Game Theory · Computer Science 2016-11-28 Hugo Gimbert , Wieslaw Zielonka

Altruistic cooperation is costly yet socially desirable. As a result, agents struggle to learn cooperative policies through independent reinforcement learning (RL). Indirect reciprocity, where agents consider their interaction partner's…

Multiagent Systems · Computer Science 2024-08-09 Martin Smit , Fernando P. Santos

This paper is concerned with the closed-loop Stackelberg strategy for linear-quadratic leader-follower game. Completely different from the open-loop and feedback Stackelberg strategy, the solvability of the closed-loop solution even the…

Optimization and Control · Mathematics 2024-03-19 Hongdan Li , Juanjuan Xu , Hunashui Zhang

We study a class of stochastic dynamic games that exhibit strategic complementarities between players; formally, in the games we consider, the payoff of a player has increasing differences between her own state and the empirical…

Computer Science and Game Theory · Computer Science 2010-12-13 Sachin Adlakha , Ramesh Johari

Learning from a partner who collects higher payoff is a frequently used working hypothesis in evolutionary game theory. One of the alternative dynamical rules is when the focal player prefers to follow the strategy choice of the majority in…

Physics and Society · Physics 2018-09-14 Attila Szolnoki , Xiaojie Chen

This paper is concerned with a linear-quadratic partially observed mean field Stackelberg stochastic differential game, which contains a leader and a large number of followers. Specifically, the followers confront a large-population Nash…

Optimization and Control · Mathematics 2025-12-09 Yu Si , Yueyang Zheng , Jingtao Shi