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We study a multi-agent setting in which brokers transact with an informed trader. Through a sequential Stackelberg-type game, brokers manage trading costs and adverse selection with an informed trader. In particular, supplying liquidity to…

Trading and Market Microstructure · Quantitative Finance 2025-11-13 Ryan Donnelly , Zi Li

This paper examines games with strategic complements or substitutes and incomplete information, where players are uncertain about the opponents' parameters. We assume that the players' beliefs about the opponent's parameters are selected…

Theoretical Economics · Economics 2025-01-28 Joep van Sloun

Two-stage Colonel Blotto game represents a typical adversarial resource allocation problem, in which two opposing agents sequentially allocate resources in a network topology across two phases: an initial resource deployment followed by…

Artificial Intelligence · Computer Science 2025-06-11 Yang Lv , Jinlong Lei , Peng Yi

In repeated games, cooperation is possible in equilibrium only if players are sufficiently patient, and long-term gains from cooperation outweigh short-term gains from deviation. What happens if the players have incomplete information…

Economics · Quantitative Finance 2019-01-23 Cy Maor , Eilon Solan

In an iterated two-person game, for instance prisoner's dilemma or the snowdrift game, there exist strategies that force the payoffs of the opponents to be equal. These equalizer strategies form a subset of the more general zero-determinant…

Populations and Evolution · Quantitative Biology 2018-08-01 Assaf Engel , Alexander Feigel

We consider the impact of incomplete information on incentives for node cooperation in parallel relay networks with one source node, one destination node, and multiple relay nodes. All nodes are selfish and strategic, interested in…

Computer Science and Game Theory · Computer Science 2011-01-24 Hongda Xiao , Edmund M. Yeh

In this work, we study the system of interacting non-cooperative two Q-learning agents, where one agent has the privilege of observing the other's actions. We show that this information asymmetry can lead to a stable outcome of population…

Machine Learning · Computer Science 2021-01-26 Ezra Tampubolon , Haris Ceribasic , Holger Boche

We study $n$-dimensional contests between two players with heterogeneous effort costs, where each dimension (battle) is modeled as a Tullock contest. Prize-allocation rules are identity-independent, budget-balanced, and weakly increasing in…

Theoretical Economics · Economics 2026-03-31 Siyuan Fan , Zhonghong Kuang , Jingfeng Lu

We study the problem of finding robust equilibria in multiplayer concurrent games with mean payoff objectives. A $(k,t)$-robust equilibrium is a strategy profile such that no coalition of size $k$ can improve the payoff of one its member by…

Computer Science and Game Theory · Computer Science 2016-02-02 Romain Brenguier

In this paper, we study the strategic allocation of limited resources using a Colonel Blotto game (CBG) under a dynamic setting and analyze the problem using an online learning approach. In this model, one of the players is a learner who…

Machine Learning · Computer Science 2023-09-13 Vincent Leon , S. Rasoul Etesami

This paper addresses information design in a workhorse model of network games, where agents have linear best responses, the information designer maximizes a quadratic objective, and the payoff-relevant state follows a multivariate Gaussian…

Theoretical Economics · Economics 2025-08-18 Masaki Miyashita , Takashi Ui

When opposing parties compete for a prize, the sunk effort players exert during the conflict can affect the value of the winner's reward. These spillovers can have substantial influence on the equilibrium behavior of participants in…

Theoretical Economics · Economics 2023-02-07 Maria Betto , Matthew W. Thomas

A recent body of experimental literature has studied empirical game-theoretical analysis, in which we have partial knowledge of a game, consisting of observations of a subset of the pure-strategy profiles and their associated payoffs to…

Computer Science and Game Theory · Computer Science 2014-02-13 John Fearnley , Martin Gairing , Paul Goldberg , Rahul Savani

When learning in strategic environments, a key question is whether agents can overcome uncertainty about their preferences to achieve outcomes they could have achieved absent any uncertainty. Can they do this solely through interactions…

Computer Science and Game Theory · Computer Science 2024-11-21 Nivasini Ananthakrishnan , Nika Haghtalab , Chara Podimata , Kunhe Yang

The paper proposes a natural measure space of zero-sum perfect information games with upper semicontinuous payoffs. Each game is specified by the game tree, and by the assignment of the active player and of the capacity to each node of the…

Computer Science and Game Theory · Computer Science 2021-04-22 János Flesch , Arkadi Predtetchinski , Ville Suomala

Data is the central commodity of the digital economy. Unlike physical goods, it is non-rival, replicable at near-zero cost, and traded under heterogeneous licensing rules. These properties defy standard supply--demand theory and call for…

Physics and Society · Physics 2025-10-13 Pasquale Casaburi , Giovanni Piccioli , Pierpaolo Vivo

We consider a two-player zero-sum stochastic differential game in which one of the players has a private information on the game. Both players observe each other, so that the non-informed player can try to guess his missing information. Our…

Probability · Mathematics 2011-06-15 Christine Grün

For a two-player imperfect-information extensive-form game (IIEFG) with $K$ time steps and a player action space of size $U$, the game tree complexity is $U^{2K}$, causing existing IIEFG solvers to struggle with large or infinite $(U,K)$,…

Computer Science and Game Theory · Computer Science 2026-03-03 Mukesh Ghimire , Lei Zhang , Zhe Xu , Yi Ren

In this paper, we study platforms where resources and jobs are spatially distributed, and resources have the flexibility to strategically move to different locations for better payoffs. The price of the service at each location depends on…

Computer Science and Game Theory · Computer Science 2023-07-18 Ozan Candogan , Manxi Wu

Single-player contextual bandits are a well-studied problem in reinforcement learning that has seen applications in various fields such as advertising, healthcare, and finance. In light of the recent work on \emph{information asymmetric}…

Machine Learning · Computer Science 2025-03-13 William Chang , Yuanhao Lu