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In a multi-agent system, transitioning from a centralized to a distributed decision-making strategy can introduce vulnerability to adversarial manipulation. We study the potential for adversarial manipulation in a class of graphical…

Computer Science and Game Theory · Computer Science 2017-11-03 Philip N. Brown , Holly Borowski , Jason R. Marden

Human behavioural patterns exhibit selfish or competitive, as well as selfless or altruistic tendencies, both of which have demonstrable effects on human social and economic activity. In behavioural economics, such effects have…

Multiagent Systems · Computer Science 2021-04-28 Jan E. Snellman , Gerardo Iñiguez , János Kertész , R. A. Barrio , Kimmo K. Kaski

We examine normal-form games in which players may \emph{pre-commit} to outcome-contingent transfers before choosing their actions. In the one-shot version of this model, Jackson and Wilkie showed that side contracting can backfire: even a…

Computer Science and Game Theory · Computer Science 2025-08-12 Ivan Geffner , Caspar Oesterheld , Vincent Conitzer

Bargaining can be used to resolve mixed-motive games in multi-agent systems. Although there is an abundance of negotiation strategies implemented in automated negotiating agents, most agents are based on single fixed strategies, while it is…

Multiagent Systems · Computer Science 2022-12-21 Bram M. Renting , Holger H. Hoos , Catholijn M. Jonker

Understanding the evolution of human social systems requires flexible formalisms for the emergence of institutions. Although game theory is normally used to model interactions individually, larger spaces of games can be helpful for modeling…

Physics and Society · Physics 2021-08-12 Seth Frey , Curtis Atkisson

Destructive agents, who opt out of the game and indiscriminately harm others, paradoxically foster cooperation, representing an intriguing variant of the voluntary participation strategy. Yet, their impact on cooperation remains…

Physics and Society · Physics 2024-09-13 Khadija Khatun , Chen Shen , Lei Shi , Jun Tanimoto

We propose an adaptive incentive mechanism that learns the optimal incentives in environments where players continuously update their strategies. Our mechanism updates incentives based on each player's externality, defined as the difference…

Computer Science and Game Theory · Computer Science 2025-03-04 Chinmay Maheshwari , Kshitij Kulkarni , Manxi Wu , Shankar Sastry

We study the canonical signaling game, endowing the sender with commitment power: before learning the state, sender designs a strategy, which maps the state into a probability distribution over actions. We provide a geometric…

Theoretical Economics · Economics 2025-02-04 Raphael Boleslavsky , Mehdi Shadmehr

To take advantage of strategy commitment, a useful tactic of playing games, a leader must learn enough information about the follower's payoff function. However, this leaves the follower a chance to provide fake information and influence…

Computer Science and Game Theory · Computer Science 2023-06-14 Yurong Chen , Xiaotie Deng , Yuhao Li

We introduce the class of pay or play games, which captures scenarios in which each decision maker is faced with a choice between two actions: one with a fixed payoff and an- other with a payoff dependent on others' selected actions. This…

Computer Science and Game Theory · Computer Science 2013-09-27 Sigal Oren , Michael Schapira , Moshe Tennenholtz

Punishment and partner switching are two well-studied mechanisms that support the evolution of cooperation. Observation of human behaviour suggests that the extent to which punishment is adopted depends on the usage of alternative…

Physics and Society · Physics 2018-04-26 Hirofumi Takesue

It is well known that a non-cooperative game may have multiple equilibria. In this paper we consider the efficiency of games, measured by the ratio between the aggregate payoff over all Nash equilibria and that over all admissible controls.…

Computer Science and Game Theory · Computer Science 2025-08-20 Jianfeng Zhang

Game theory serves as a powerful tool for distributed optimization in multi-agent systems in different applications. In this paper we consider multi-agent systems that can be modeled by means of potential games whose potential function…

Optimization and Control · Mathematics 2018-04-13 Tatiana Tatarenko

This paper examines equilibria in dynamic two-sided matching games, extending Gale and Shapley's foundational model to a non-cooperative, decentralized, and dynamic framework. We focus on markets where agents have utility functions and…

Theoretical Economics · Economics 2024-12-02 Nadia Guiñazú , Pablo Neme , Jorge Oviedo

We develop a general game-theoretic framework for reasoning about strategic agents performing possibly costly computation. In this framework, many traditional game-theoretic results (such as the existence of a Nash equilibrium) no longer…

Computer Science and Game Theory · Computer Science 2008-09-02 Joseph Y. Halpern , Rafael Pass

In the study of reactive systems, qualitative properties are usually easier to model and analyze than quantitative properties. This is especially true in systems where mutually beneficial cooperation between agents is possible, such as…

Computer Science and Game Theory · Computer Science 2023-05-18 Senthil Rajasekaran , Suguman Bansal , Moshe Y. Vardi

We consider an online regression setting in which individuals adapt to the regression model: arriving individuals are aware of the current model, and invest strategically in modifying their own features so as to improve the predicted score…

Machine Learning · Computer Science 2021-03-02 Yahav Bechavod , Katrina Ligett , Zhiwei Steven Wu , Juba Ziani

A generalized model of games is proposed, in which cooperative games and non-cooperative games are special cases. Some games that are neither cooperative nor non-cooperative can be expressed and analyzed. The model is based on relationships…

Computer Science and Game Theory · Computer Science 2016-10-10 Jiawei Li

It is clear that one of the primary tools we can use to mitigate the potential risk from a misbehaving AI system is the ability to turn the system off. As the capabilities of AI systems improve, it is important to ensure that such systems…

Artificial Intelligence · Computer Science 2017-06-19 Dylan Hadfield-Menell , Anca Dragan , Pieter Abbeel , Stuart Russell

This paper explores the use of Generative Pre-trained Transformers (GPT) in strategic game experiments, specifically the ultimatum game and the prisoner's dilemma. I designed prompts and architectures to enable GPT to understand the game…

General Economics · Economics 2023-12-12 Fulin Guo