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Related papers: Potential Games Design Using Local Information

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Computer games represent an ideal research domain for the next generation of personalized digital applications. This paper presents a player-centered framework of AI for game personalization, complementary to the commonly used…

Artificial Intelligence · Computer Science 2021-02-16 Jichen Zhu , Santiago Ontañón

We study two-player games on finite graphs. Turn-based games have many nice properties, but concurrent games are harder to tame: e.g. turn-based stochastic parity games have positional optimal strategies, whereas even basic concurrent…

Computer Science and Game Theory · Computer Science 2023-11-27 Benjamin Bordais , Patricia Bouyer , Stéphane Le Roux

We introduce a method based on the Public Goods Game for solving optimization tasks. In particular, we focus on the Traveling Salesman Problem, i.e. a NP-hard problem whose search space exponentially grows increasing the number of cities.…

Physics and Society · Physics 2017-08-30 Marco Alberto Javarone

Quantum game theory is the study of strategic behavior by agents with access to quantum technology. Broadly speaking, this technology can be employed in either of two ways: As part of a randomization device or as part of a communications…

Optimization and Control · Mathematics 2011-10-31 Steven E. Landsburg

Strategic diversity is often essential in games: in multi-player games, for example, evaluating a player against a diverse set of strategies will yield a more accurate estimate of its performance. Furthermore, in games with…

Artificial Intelligence · Computer Science 2021-10-11 Marta Garnelo , Wojciech Marian Czarnecki , Siqi Liu , Dhruva Tirumala , Junhyuk Oh , Gauthier Gidel , Hado van Hasselt , David Balduzzi

Strategic interactions between a group of individuals or organisations can be modelled as games played on networks, where a player's payoff depends not only on their actions but also on those of their neighbours. Inferring the network…

Machine Learning · Computer Science 2022-08-19 Emanuele Rossi , Federico Monti , Yan Leng , Michael M. Bronstein , Xiaowen Dong

Decentralised optimisation tasks are important components of multi-agent systems. These tasks can be interpreted as n-player potential games: therefore game-theoretic learning algorithms can be used to solve decentralised optimisation…

Multiagent Systems · Computer Science 2013-01-16 Michalis Smyrnakis

Attribute-driven software architecture design aims to provide decision support by taking into account the quality attributes of softwares. A central question in this process is: What architecture design best fulfills the desirable software…

Computer Science and Game Theory · Computer Science 2015-08-13 Jiamou Liu , Ziheng Wei

Often adaptive, distributed control can be viewed as an iterated game between independent players. The coupling between the players' mixed strategies, arising as the system evolves from one instant to the next, is determined by the system…

Multiagent Systems · Computer Science 2007-05-23 David H. Wolpert , Stefan Bieniawski

The problem of solving a parity game is at the core of many problems in model checking, satisfiability checking and program synthesis. Some of the best algorithms for solving parity game are strategy improvement algorithms. These are global…

Computer Science and Game Theory · Computer Science 2010-06-09 Oliver Friedmann , Martin Lange

We present a causality-based algorithm for solving two-player reachability games represented by logical constraints. These games are a useful formalism to model a wide array of problems arising, e.g., in program synthesis. Our technique for…

Logic in Computer Science · Computer Science 2021-06-01 Christel Baier , Norine Coenen , Bernd Finkbeiner , Florian Funke , Simon Jantsch , Julian Siber

We study security threats to Markov games due to information asymmetry and misinformation. We consider an attacker player who can spread misinformation about its reward function to influence the robust victim player's behavior. Given a…

Machine Learning · Computer Science 2024-06-26 Jeremy McMahan , Young Wu , Yudong Chen , Xiaojin Zhu , Qiaomin Xie

We investigate a multi-agent decision-making problem where a large population of agents is responsible for carrying out a set of assigned tasks. The amount of jobs in each task varies over time governed by a dynamical system model. Each…

Systems and Control · Electrical Eng. & Systems 2023-09-19 Shinkyu Park , Julian Barreiro-Gomez

This paper considers games where the utilities for agents are the sum of a term proportional to a social utility, and another term that is an individual cost or reward. The agents are assumed to be irrational in their perception of the…

Computer Science and Game Theory · Computer Science 2026-05-21 Ashok Krishnan K. S. , Helene Le Cadre , Ana Busic

In this paper, we study inverse game theory (resp. inverse multiagent learning) in which the goal is to find parameters of a game's payoff functions for which the expected (resp. sampled) behavior is an equilibrium. We formulate these…

Computer Science and Game Theory · Computer Science 2025-02-21 Denizalp Goktas , Amy Greenwald , Sadie Zhao , Alec Koppel , Sumitra Ganesh

Game theory has been developed by scientists as a theory of strategic interaction among players who are supposed to be perfectly rational. These strategic interactions might have been presented in an auction, a business negotiation, a chess…

Computer Science and Game Theory · Computer Science 2020-04-07 Medet Kanmaz , Elif Surer

Wireless communication networks are becoming highly virtualized with two-layer hierarchies, in which controllers at the upper layer with tasks to achieve can ask a large number of agents at the lower layer to help realize computation,…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-11-07 Zijie Zheng , Lingyang Song , Zhu Han , Geoffrey Ye Li , H. Vincent Poor

Strategy iteration is a technique frequently used for two-player games in order to determine the winner or compute payoffs, but to the best of our knowledge no general framework for strategy iteration has been considered. Inspired by…

Logic in Computer Science · Computer Science 2022-12-14 Paolo Baldan , Richard Eggert , Barbara König , Tommaso Padoan

Min-max problems are important in multi-agent sequential decision-making because they improve the performance of the worst-performing agent in the network. However, solving the multi-agent min-max problem is challenging. We propose a…

Multiagent Systems · Computer Science 2024-05-31 Alexandros E. Tzikas , Jinkyoo Park , Mykel J. Kochenderfer , Ross E. Allen

Multi-agent systems are prevalent in a wide range of domains including power systems, vehicular networks, and robotics. Two important problems to solve in these types of systems are how the intentions of non-coordinating agents can be…

Multiagent Systems · Computer Science 2025-09-30 Benjamin Alcorn , Eman Hammad
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