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This paper studies the rational synthesis problem for multi-player games played on graphs when rational players are following subgame perfect equilibria. In these games, one player, the system, declares his strategy upfront, and the other…

Computer Science and Game Theory · Computer Science 2025-07-16 Véronique Bruyère , Jean-François Raskin , Alexis Reynouard , Marie Van Den Bogaard

In this work we offer an $O(|V|^2 |E|\, W)$ pseudo-polynomial time deterministic algorithm for solving the Value Problem and Optimal Strategy Synthesis in Mean Payoff Games. This improves by a factor $\log(|V|\, W)$ the best previously…

Data Structures and Algorithms · Computer Science 2016-04-26 Carlo Comin , Romeo Rizzi

We consider a randomized algorithm for the unique games problem, using independent multinomial probabilities to assign labels to the vertices of a graph. The expected value of the solution obtained by the algorithm is expressed as a…

Computational Complexity · Computer Science 2015-08-10 Rajeev Kohli , Ramesh Krishnamurti

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

We investigate the computation of equilibria in extensive-form games where ex ante correlation is possible, focusing on correlated equilibria requiring the least amount of communication between the players and the mediator. Motivated by the…

Computer Science and Game Theory · Computer Science 2019-01-21 Andrea Celli , Stefano Coniglio , Nicola Gatti

For $f$ a weighted voting scheme used by $n$ voters to choose between two candidates, the $n$ \emph{Shapley-Shubik Indices} (or {\em Shapley values}) of $f$ provide a measure of how much control each voter can exert over the overall outcome…

Computer Science and Game Theory · Computer Science 2012-12-21 Anindya De , Ilias Diakonikolas , Rocco A. Servedio

Computing approximate Nash equilibria in multi-player general-sum Markov games is a computationally intractable task. However, multi-player Markov games with certain cooperative or competitive structures might circumvent this…

Computer Science and Game Theory · Computer Science 2023-08-17 Zailin Ma , Jiansheng Yang , Zhihua Zhang

Randomized search heuristics such as evolutionary algorithms are frequently applied to dynamic combinatorial optimization problems. Within this paper, we present a dynamic model of the classic Weighted Vertex Cover problem and analyze the…

Neural and Evolutionary Computing · Computer Science 2020-01-27 Feng Shi , Frank Neumann , Jianxin Wang

We introduce new power indices to measure the a priori voting power of voters in liquid democracy elections where an underlying network restricts delegations. We argue that our power indices are natural extensions of the standard…

Multiagent Systems · Computer Science 2023-05-16 Rachael Colley , Théo Delemazure , Hugo Gilbert

We provide a unifying, black-box tool for establishing existence of approximate equilibria in weighted congestion games and, at the same time, bounding their Price of Stability. Our framework can handle resources with general…

Computer Science and Game Theory · Computer Science 2022-03-31 Yiannis Giannakopoulos , Diogo Poças

The winner determination problems of many attractive multi-winner voting rules are NP-complete. However, they often admit polynomial-time algorithms when restricting inputs to be single-peaked. Commonly, such algorithms employ dynamic…

Computer Science and Game Theory · Computer Science 2021-04-20 Dominik Peters

Solving parity games is a major building block for numerous applications in reactive program verification and synthesis. While they can be solved efficiently in practice, no known approach has a polynomial worst-case runtime complexity. We…

Computer Science and Game Theory · Computer Science 2023-07-28 Tobias Hecking , Swathy Muthukrishnan , Alexander Weinert

In this paper, a novel approach for the optimal combination of binary classifiers is proposed. The classifier combination problem is approached from a Game Theory perspective. The proposed framework of adapted weighted majority rules (WMR)…

Machine Learning · Computer Science 2013-02-05 Harris V. Georgiou , Michael E. Mavroforakis

We study the computational complexity of the map redistricting problem (gerrymandering). Mathematically, the electoral district designer (gerrymanderer) attempts to partition a weighted graph into $k$ connected components (districts) such…

Computer Science and Game Theory · Computer Science 2024-01-09 Jack Dippel , Max Dupré la Tour , April Niu , Sanjukta Roy , Adrian Vetta

The Banzhaf Power Index (BPI) is a method of measuring the power of voters in determining the outcome of a voting game. Some voting games exhibit a hierarchical structure, including the US electoral college and ensemble learning methods; we…

Computer Science and Game Theory · Computer Science 2025-01-14 John Randolph , Denizalp Goktas , Amy Greenwald

Maximum weight matching is one of the most fundamental combinatorial optimization problems with a wide range of applications in data mining and bioinformatics. Developing distributed weighted matching algorithms is challenging due to the…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-06-06 Sepehr Assadi , MohammadHossein Bateni , Vahab Mirrokni

We introduce a new simple game, which is referred to as the complementary weighted multiple majority game (C-WMMG for short). C-WMMG models a basic cooperation rule, the complementary cooperation rule, and can be taken as a sister model of…

Computer Science and Game Theory · Computer Science 2013-01-04 Zhigang Cao , Xiaoguang Yang

The problem of computing a common point that lies in the intersection of a finite number of closed convex sets, each known to one agent in a network, is studied. This issue, known as the distributed convex feasibility problem or the…

Multiagent Systems · Computer Science 2020-08-11 Dimitris Ampeliotis , Kostas Berberidis

Optimal policies in standard MDPs can be obtained using either value iteration or policy iteration. However, in the case of zero-sum Markov games, there is no efficient policy iteration algorithm; e.g., it has been shown that one has to…

Machine Learning · Computer Science 2023-10-31 Anna Winnicki , R. Srikant

Let $G = (N,E,w)$ be a weighted communication graph (with weight function $w$ on $E$). For every subset $A \subseteq N$, we delete in the subset $E(A)$ of edges with ends in $A$, all edges of minimum weight in $E(A)$. Then the connected…

Discrete Mathematics · Computer Science 2016-08-26 Alexandre Skoda
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