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Recently, strategic games inspired by Schelling's influential model of residential segregation have been studied in the TCS and AI literature. In these games, agents of k different types occupy the nodes of a network topology aiming to…

Computer Science and Game Theory · Computer Science 2024-03-15 Lata Narayanan , Yasaman Sabbagh , Alexandros A. Voudouris

Under certain circumstances such as lack of information or bounded rationality, human players can take decisions on which strategy to choose in a game on the basis of simple opinions. These opinions can be modified after each round by…

Physics and Society · Physics 2015-06-05 Floriana Gargiulo , Jose J. Ramasco

We examine the issue of stability of probability in reasoning about complex systems with uncertainty in structure. Normally, propositions are viewed as probability functions on an abstract random graph where it is implicitly assumed that…

Artificial Intelligence · Computer Science 2017-12-14 Subhash Kak

We use the indirect evolutionary approach to study evolutionarily stable preferences against multiple mutations in single- and multi-population matching settings, respectively. Players choose strategies to maximize their subjective…

Computer Science and Game Theory · Computer Science 2025-07-08 Yu-Sung Tu , Wei-Torng Juang

Optimizing strategic decisions (a.k.a. computing equilibrium) is key to the success of many non-cooperative multi-agent applications. However, in many real-world situations, we may face the exact opposite of this game-theoretic problem --…

Computer Science and Game Theory · Computer Science 2022-10-05 Jibang Wu , Weiran Shen , Fei Fang , Haifeng Xu

Strategic reasoning enables agents to cooperate, communicate, and compete with other agents in diverse situations. Existing approaches to solving strategic games rely on extensive training, yielding strategies that do not generalize to new…

Artificial Intelligence · Computer Science 2023-05-31 Kanishk Gandhi , Dorsa Sadigh , Noah D. Goodman

We study the quality of outcomes in repeated games when the population of players is dynamically changing and participants use learning algorithms to adapt to the changing environment. Game theory classically considers Nash equilibria of…

Computer Science and Game Theory · Computer Science 2020-05-25 Thodoris Lykouris , Vasilis Syrgkanis , Eva Tardos

Infinite games where several players seek to coordinate under imperfect information are known to be intractable, unless the information flow is severely restricted. Examples of undecidable cases typically feature a situation where players…

Logic in Computer Science · Computer Science 2014-05-01 Dietmar Berwanger , Anup Basil Mathew

Human societies around the world interact with each other by developing and maintaining social norms, and it is critically important to understand how such norms emerge and change. In this work, we define an evolutionary game-theoretic…

Computers and Society · Computer Science 2017-04-18 Soham De , Dana S. Nau , Michele J. Gelfand

Given a dynamic ordinal game, we deem a strategy sequentially rational if there exist a Bernoulli utility function and a conditional probability system with respect to which the strategy is a maximizer. We establish a complete class theorem…

Theoretical Economics · Economics 2023-12-07 Pierfrancesco Guarino

Multi-agent systems are designed to concurrently accomplish a diverse set of tasks at unprecedented scale. Here, the central problems faced by a system operator are to decide (i) how to divide available resources amongst the agents assigned…

Systems and Control · Electrical Eng. & Systems 2021-04-01 Keith Paarporn , Rahul Chandan , Mahnoosh Alizadeh , Jason R. Marden

We introduce a new solution concept, called periodicity, for selecting optimal strategies in strategic form games. This periodicity solution concept yields new insight into non-trivial games. In mixed strategy strategic form games, periodic…

Computer Science and Game Theory · Computer Science 2020-06-30 V. K. Oikonomou , J. Jost

In the naming game, individuals or agents exchange pairwise local information in order to communicate about objects in their common environment. The goal of the game is to reach a consensus about naming these objects. Originally used to…

Multiagent Systems · Computer Science 2009-12-24 Reginaldo J. da Silva Filho , Matthias R. Brust , Carlos H. C. Ribeiro

We investigate the dynamics of the choice of an active strategy in the minority game. A history distribution is introduced as an analytical tool to study the asymmetry between the two choices offered to the agents. Its properties are…

adap-org · Physics 2009-10-31 R. D'Hulst , G. J. Rodgers

The key challenge in multiagent learning is learning a best response to the behaviour of other agents, which may be non-stationary: if the other agents adapt their strategy as well, the learning target moves. Disparate streams of research…

Multiagent Systems · Computer Science 2019-03-13 Pablo Hernandez-Leal , Michael Kaisers , Tim Baarslag , Enrique Munoz de Cote

Programs that combine I/O and countable probabilistic choice, modulo either bisimilarity or trace equivalence, can be seen as describing a probabilistic strategy. For well-founded programs, we might expect to axiomatize bisimilarity via a…

Logic in Computer Science · Computer Science 2025-08-22 Nathan Bowler , Sergey Goncharov , Paul Blain Levy

We study turn-based quantitative games of infinite duration opposing two antagonistic players and played over graphs. This model is widely accepted as providing the adequate framework for formalizing the synthesis question for reactive…

Computer Science and Game Theory · Computer Science 2023-06-22 Pierre Ohlmann

Infinitely repeated games support equilibrium concepts beyond those present in one-shot games (e.g., cooperation in the prisoner's dilemma). Nonetheless, repeated games fail to capture our real-world intuition for settings with many…

Computer Science and Game Theory · Computer Science 2025-05-22 Henry Fleischmann , Kiriaki Fragkia , Ratip Emin Berker

Many applications require the robustness, or ideally the invariance, of a neural network to certain transformations of input data. Most commonly, this requirement is addressed by either augmenting the training data, using adversarial…

Computer Vision and Pattern Recognition · Computer Science 2021-06-21 Kanchana Vaishnavi Gandikota , Jonas Geiping , Zorah Lähner , Adam Czapliński , Michael Moeller

Program behavior may depend on parameters, which are either configured before compilation time, or provided at run-time, e.g., by sensors or other input devices. Parametric program analysis explores how different parameter settings may…

Programming Languages · Computer Science 2014-06-23 Thomas M. Gawlitza , Martin D. Schwarz , Helmut Seidl
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