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We consider a multi-organizational system in which each organization contributes processors to the global pool but also jobs to be processed on the common resources. The fairness of the scheduling algorithm is essential for the stability…

分布式、并行与集群计算 · 计算机科学 2014-04-23 Piotr Skowron , Krzysztof Rzadca

Modern transformer attention is internally multi-agent -- heads compete and coordinate -- yet we train it as if it were a monolithic optimizer. We formalize this gap: cross-entropy training induces an implicit potential game among heads,…

人工智能 · 计算机科学 2026-02-03 Kushal Chakrabarti , Nirmal Balachundar

In repeated interactions between individuals, we do not expect that exactly the same situation will occur from one time to another. Contrary to what is common in models of repeated games in the literature, most real situations may differ a…

种群与进化 · 定量生物学 2007-05-23 Anders Eriksson , Kristian Lindgren

We introduce a new measure of the discrepancy in strategic games between the social welfare in a Nash equilibrium and in a social optimum, that we call selfishness level. It is the smallest fraction of the social welfare that needs to be…

计算机科学与博弈论 · 计算机科学 2014-04-04 Krzysztof R. Apt , Guido Schaefer

Given that the assumption of perfect rationality is rarely met in the real world, we explore a graded notion of rationality in socioecological systems of networked actors. We parametrize an actors' rationality via their place in a social…

物理与社会 · 物理学 2017-05-15 Sabin Roman , Markus Brede

In this study, we formulate positive and negative externalities caused by changes in the supply of shared vehicles as ride sharing games. The study aims to understand the price of anarchy (PoA) and its improvement via a coordination…

计算机科学与博弈论 · 计算机科学 2016-04-05 Tatsuya Iwase , Takahiro Shiga

We consider 2-player games played on a finite state space for infinite rounds. The games are concurrent: in each round, the two players choose their moves simultaneously; the current state and the moves determine the successor. We consider…

计算机科学与博弈论 · 计算机科学 2013-06-21 Krishnendu Chatterjee

The price of anarchy (PoA) is a popular metric for analyzing the inefficiency of self-interested decision making. Although its study is widespread, characterizing the PoA can be challenging. A commonly employed approach is based on the…

计算机科学与博弈论 · 计算机科学 2021-05-26 Rahul Chandan , Dario Paccagnan , Jason R. Marden

We study two natural problems about rational behaviors in multiplayer non-zero-sum sequential infinite duration games played on graphs: checking problems, that consist in deciding whether a strategy profile, defined by a Mealy machine, is…

计算机科学与博弈论 · 计算机科学 2023-07-17 Léonard Brice , Jean-François Raskin , Marie van den Bogaard

A basic lesson from game theory is that strategic behavior often renders the equilibrium outcome inefficient. The recent literature of information design -- a.k.a. signaling or persuasion -- looks to improve equilibria by providing…

计算机科学与博弈论 · 计算机科学 2020-09-29 James Nachbar , Haifeng Xu

We examine sequential equilibrium in the context of computational games, where agents are charged for computation. In such games, an agent can rationally choose to forget, so issues of imperfect recall arise. In this setting, we consider…

计算机科学与博弈论 · 计算机科学 2014-12-22 Joseph Y. Halpern , Rafael Pass

We investigate multi-organizational scheduling problems, building upon the framework introduced by Pascual et al.[2009]. In this setting, multiple organizations each own a set of identical machines and sequential jobs with distinct…

计算机科学与博弈论 · 计算机科学 2025-05-20 Jiehua Chen , Martin Durand , Christian Hatschka

We introduce a framework for studying the effect of cooperation on the quality of outcomes in utility games. Our framework is a coalitional analog of the smoothness framework of non-cooperative games. Coalitional smoothness implies bounds…

计算机科学与博弈论 · 计算机科学 2013-07-10 Yoram Bachrach , Vasilis Syrgkanis , Eva Tardos , Milan Vojnovic

We consider the well-studied game-theoretic version of machine scheduling in which jobs correspond to self-interested users and machines correspond to resources. Here each user chooses a machine trying to minimize her own cost, and such…

计算机科学与博弈论 · 计算机科学 2019-12-18 Cong Chen , Paolo Penna , Yinfeng Xu

There have been great efforts in studying the cascading behavior in social networks such as the innovation diffusion, etc. Game theoretically, in a social network where individuals choose from two strategies: A (the innovation) and B (the…

计算机科学与博弈论 · 计算机科学 2014-07-29 Xilun Chen , Chenxia Wu

Standard models of bounded rationality typically assume agents either possess accurate knowledge of the population's reasoning abilities (Cognitive Hierarchy) or hold dogmatic, degenerate beliefs (Level-$k$). We introduce the ``Connected…

计算机科学与博弈论 · 计算机科学 2026-02-13 Raman Ebrahimi , Sepehr Ilami , Babak Heydari , Isabel Trevino , Massimo Franceschetti

We consider an atomic congestion game in which each player $i$ participates in the game with an exogenous and known probability $p_{i}\in(0,1]$, independently of everybody else, or stays out and incurs no cost. We compute the parameterized…

计算机科学与博弈论 · 计算机科学 2024-08-13 Roberto Cominetti , Marco Scarsini , Marc Schröder , Nicolás Stier-Moses

Rationality is frequently associated with making the best possible decisions. It's widely acknowledged that humans, as rational beings, have limitations in their decision-making capabilities. Nevertheless, recent advancements in fields,…

计算机与社会 · 计算机科学 2023-11-03 Dibakar Das

In congestion games, selfish users behave myopically to crowd to the shortest paths, and the social planner designs mechanisms to regulate such selfish routing through information or payment incentives. However, such mechanism design…

计算机科学与博弈论 · 计算机科学 2025-01-15 Hongbo Li , Lingjie Duan

This work focuses on the design of taxes in atomic congestion games, a commonly studied model for competitive resource sharing. While most related studies focus on optimizing either the worst- or best-case performance (i.e., Price of…

计算机科学与博弈论 · 计算机科学 2023-04-14 Rahul Chandan , Dario Paccagnan , Jason R. Marden