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We propose a type of non-cooperative game, termed multi-cluster aggregative game, which is composed of clusters as players, where each cluster consists of collaborative agents with cost functions depending on their own decisions and the…

Multiagent Systems · Computer Science 2023-05-16 Yue Chen , Peng Yi

This paper investigates design of noncooperative games from an optimization and control theoretic perspective. Pricing mechanisms are used as a design tool to ensure that the Nash equilibrium of a fairly general class of noncooperative…

Computer Science and Game Theory · Computer Science 2010-07-02 Tansu Alpcan , Lacra Pavel , Nem Stefanovic

This work studies the decentralized and uncoordinated energy source selection problem for smart-grid consumers with heterogeneous energy profiles and risk attitudes: they compete for a limited amount of renewable energy in their local…

Systems and Control · Electrical Eng. & Systems 2022-03-16 Eleni Stai , Evangelia Kokolaki , Lesia Mitridati , Petros Tatoulis , Ioannis Stavrakakis , Gabriela Hug

We study the role of correlation in matching markets, where multiple decision-makers simultaneously face selection problems from the same pool of candidates. We propose a model in which a candidate's priority scores across different…

Computer Science and Game Theory · Computer Science 2025-12-08 Rémi Castera , Patrick Loiseau , Bary S. R. Pradelski

We study a heterogeneous agent macroeconomic model with an infinite number of households and firms competing in a labor market. Each household earns income and engages in consumption at each time step while aiming to maximize a concave…

General Economics · Economics 2023-03-10 Ruitu Xu , Yifei Min , Tianhao Wang , Zhaoran Wang , Michael I. Jordan , Zhuoran Yang

We formulate two-party policy competition as a two-player non-cooperative game, generalizing Lin et al.'s work (2021). Each party selects a real-valued policy vector as its strategy from a compact subset of Euclidean space, and a voter's…

Computer Science and Game Theory · Computer Science 2026-03-19 Chuang-Chieh Lin , Chi-Jen Lu , Po-An Chen , Chih-Chieh Hung

Most existing notions of algorithmic fairness are one-shot: they ensure some form of allocative equality at the time of decision making, but do not account for the adverse impact of the algorithmic decisions today on the long-term welfare…

Computers and Society · Computer Science 2019-06-28 Hoda Heidari , Vedant Nanda , Krishna P. Gummadi

We study optimal execution in markets with transient price impact in a competitive setting with $N$ traders. Motivated by prior negative results on the existence of pure Nash equilibria, we consider randomized strategies for the traders and…

Trading and Market Microstructure · Quantitative Finance 2026-05-19 Steven Campbell , Marcel Nutz

We study a variant of the Hotelling-Downs model of spatial competition between firms where consumer choices are influenced by their individual preferences as well as the popularity of the firms. In general, a multiplicity of market…

Computer Science and Game Theory · Computer Science 2024-01-17 Gaëtan Fournier , Marc Schröder

We consider the process of bidding by electricity suppliers in a day-ahead market context where each supplier bids a linear non-decreasing function of her generating capacity with the goal of maximizing her individual profit given other…

Optimization and Control · Mathematics 2018-11-16 Ruidi Chen , Ioannis Ch. Paschalidis , Michael C. Caramanis , Panagiotis Andrianesis

Congestion is a common failure mode of markets, where consumers compete inefficiently on the same subset of goods (e.g., chasing the same small set of properties on a vacation rental platform). The typical economic story is that prices…

Machine Learning · Computer Science 2024-04-04 Omer Nahum , Gali Noti , David Parkes , Nir Rosenfeld

To what extent does the structure of the players' strategy space influence the efficiency of decentralized solutions in congestion games? In this work, we investigate whether better performance are possible when restricting to load…

Computer Science and Game Theory · Computer Science 2022-02-25 Vittorio Bilò , Cosimo Vinci

In the modern age of large-scale AI, federated learning has become an increasingly important tool for training large populations of AI agents; however, its computational and communication costs can rapidly fail to scale with the number of…

Machine Learning · Computer Science 2026-05-08 Xuwei Yang , David B. Emerson , Fatemeh Tavakoli , Anastasis Kratsios

Distributed Nash equilibrium (NE) seeking problem for multi-coalition games has attracted increasing attention in recent years, but the research mainly focuses on the case without agreement demand within coalitions. This paper considers a…

Optimization and Control · Mathematics 2021-12-10 Jialing Zhou , Yuezu Lv , Guanghui Wen , Jinhu Lv , Dezhi Zheng

The decisions that human beings make to allocate time has significant bearing on economic output and to the sustenance of social networks. The time allocation problem motivates our formal analysis of the resource allocation game, where…

Computer Science and Game Theory · Computer Science 2018-08-28 Wei-Chun Lee , Vasilis Livanos , Ruta Mehta , Hari Sundaram

Efficient allocation and use of limited resources are fundamental to advancing collective welfare and achieving long-term societal sustainability. This challenge involves not only how policymakers distribute scarce resources among…

Computer Science and Game Theory · Computer Science 2026-03-18 Juyi Li , Xiaoqun Wu , Qi Su

The long-term impact of algorithmic decision making is shaped by the dynamics between the deployed decision rule and individuals' response. Focusing on settings where each individual desires a positive classification---including many…

Computer Science and Game Theory · Computer Science 2019-10-10 Lydia T. Liu , Ashia Wilson , Nika Haghtalab , Adam Tauman Kalai , Christian Borgs , Jennifer Chayes

Motivated by agentic markets -- two-sided markets in which consumers and businesses are assisted by AI tools that facilitate consumers' search -- we study the impact of improved search technology on learning and welfare in markets. We put…

Computer Science and Game Theory · Computer Science 2026-03-30 Brendan Lucier , Nicole Immorlica , Markus Mobius , Aleksandrs Slivkins , Daniel G. Goldstein , Jake M. Hofman , Sonia Jaffe , David M. Rothschild

In this paper, we address the challenge of Nash equilibrium (NE) seeking in non-cooperative convex games with partial-decision information. We propose a distributed algorithm, where each agent refines its strategy through projected-gradient…

Computer Science and Game Theory · Computer Science 2023-09-15 Duong Thuy Anh Nguyen , Mattia Bianchi , Florian Dörfler , Duong Tung Nguyen , Angelia Nedić

The control of large-scale, multi-agent systems often entails distributing decision-making across the system components. However, with advances in communication and computation technologies, we can consider new collaborative decision-making…

Computer Science and Game Theory · Computer Science 2024-07-04 Bryce L. Ferguson , Dario Paccagnan , Bary S. R. Pradelski , Jason R. Marden