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In this paper, we introduce a natural learning rule for mean field games with finite state and action space, the so-called myopic adjustment process. The main motivation for these considerations are the complex computations necessary to…

Optimization and Control · Mathematics 2020-09-01 Berenice Anne Neumann

In this paper, we consider a first-order deterministic mean field game model inspired by crowd motion in which agents moving in a given domain aim to reach a given target set in minimal time. To model interaction between agents, we assume…

Optimization and Control · Mathematics 2022-02-21 Saeed Sadeghi Arjmand , Guilherme Mazanti

A new agent-based, bounded-confidence model for discrete one-dimensional opinion dynamics is presented. The agents interact if their opinions do not differ more than a tolerance parameter. In pairwise interactions, one of the pair, randomly…

Adaptation and Self-Organizing Systems · Physics 2013-02-19 M. Kaan Öztürk

We study the problem of finding equilibrium strategies in multi-agent games with incomplete payoff information, where the payoff matrices are only known to the players up to some bounded uncertainty sets. In such games, an ex-post…

Computer Science and Game Theory · Computer Science 2020-07-14 Wenshuo Guo , Mihaela Curmei , Serena Wang , Benjamin Recht , Michael I. Jordan

Standard game theory assumes that the structure of the game is common knowledge among players. We relax this assumption by considering extensive games where agents may be unaware of the complete structure of the game. In particular, they…

Computer Science and Game Theory · Computer Science 2007-05-23 Joseph Y. Halpern , Leandro C. Rêgo

Contingency planning, wherein an agent generates a set of possible plans conditioned on the outcome of an uncertain event, is an increasingly popular way for robots to act under uncertainty. In this work we take a game-theoretic perspective…

In a dynamic matching market, such as a marriage or job market, how should agents balance accepting a proposed match with the cost of continuing their search? We consider this problem in a discrete setting, in which agents have cardinal…

Computer Science and Game Theory · Computer Science 2021-06-16 Ishan Agarwal , Richard Cole , Yixin Tao

In this paper, we present a conceptual model game to examine the dynamics of asymmetric interactions in games with imperfect information. The game involves two agents with starkly contrasting capabilities: one agent can take actions but has…

Multiagent Systems · Computer Science 2025-01-09 Fabian Farestam , Dilian Gurov

We explore a mechanism of decision-making in Mean Field Games with myopic players. At each instant, agents set a strategy which optimizes their expected future cost by assuming their environment as immutable. As the system evolves, the…

Optimization and Control · Mathematics 2018-02-05 Charafeddine Mouzouni

In this paper, we develop an agent-based version of the Diamond search equilibrium model - also called Coconut Model. In this model, agents are faced with production decisions that have to be evaluated based on their expectations about the…

Economics · Quantitative Finance 2016-12-02 Sven Banisch , Eckehard Olbrich

Although recent work in AI has made great progress in solving large, zero-sum, extensive-form games, the underlying assumption in most past work is that the parameters of the game itself are known to the agents. This paper deals with the…

Machine Learning · Computer Science 2018-06-29 Chun Kai Ling , Fei Fang , J. Zico Kolter

We study a model of competition among nomadic agents for time-varying and location-specific resources, arising in crowd-sourced transportation services, online communities, and traditional location-based economic activity. This model…

Computer Science and Game Theory · Computer Science 2018-08-17 Pu Yang , Krishnamurthy Iyer , Peter Frazier

Autonomous agents powered by large language models (LLMs) enable novel use cases in domains where responsible action is increasingly important. Yet the inherent unpredictability of LLMs raises safety concerns about agent reliability. In…

Artificial Intelligence · Computer Science 2025-05-19 Jan Chojnacki

We consider a coalition formation setting where each agent belongs to one of the two types, and agents' preferences over coalitions are determined by the fraction of the agents of their own type in each coalition. This setting differs from…

Computer Science and Game Theory · Computer Science 2019-03-04 Robert Bredereck , Edith Elkind , Ayumi Igarashi

Complex interactions among agents present a significant challenge for autonomous driving in real-world scenarios. Recently, a promising approach has emerged, which formulates the interactions of agents as a level-k game framework. It…

Artificial Intelligence · Computer Science 2025-06-09 Yesheng Zhang , Wenjian Sun , Yuheng Chen , Qingwei Liu , Qi Lin , Rui Zhang , Xu Zhao

Rating strategies in a game is an important area of research in game theory and artificial intelligence, and can be applied to any real-world competitive or cooperative setting. Traditionally, only transitive dependencies between strategies…

Computer Science and Game Theory · Computer Science 2022-10-06 Luke Marris , Marc Lanctot , Ian Gemp , Shayegan Omidshafiei , Stephen McAleer , Jerome Connor , Karl Tuyls , Thore Graepel

Designing socially optimal policies in multi-agent environments is a fundamental challenge in both economics and artificial intelligence. This paper studies a general framework for learning Stackelberg equilibria in dynamic and uncertain…

Systems and Control · Electrical Eng. & Systems 2025-09-23 Jun He , Andrew L. Liu , Yihsu Chen

We consider seeking a Nash equilibrium (NE) of a monotone game, played by dynamic agents which are modeled as a class of lower-triangular nonlinear uncertain dynamics with external disturbances. We establish a general framework that…

Optimization and Control · Mathematics 2025-11-04 Weijian Li , Yutao Tang

In this paper, we investigate the seeking of Nash equilibrium (NE) in a non-cooperative quadratic game where all agents exchange their delayed strategy information with their neighbors. To extend best-response algorithms to the delayed…

Systems and Control · Electrical Eng. & Systems 2026-02-24 Kaichen Jiang , Yuyue Yan , Mingda Yue , Yuhu Wu

The spontaneous behavioral changes of the agents during an epidemic can have significant effects on the delay and the prevalence of its spread. In this work, we study a social distancing game among the agents of a population, who determine…

Physics and Society · Physics 2020-07-13 A. -R. Lagos , I. Kordonis , G. P. Papavassilopoulos