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We revisit games in partition function form, i.e. cooperative games where the payoff of a coalition depends on the partition of the entire set of players. We assume that each coalition computes its worth having probabilistic beliefs over…

Computer Science and Game Theory · Computer Science 2026-05-05 Paraskevas V. Lekeas , Giorgos Stamatopoulos

Cooperative interval games are a generalized model of cooperative games in which the worth of every coalition corresponds to a closed interval representing the possible outcomes of its cooperation. Selections are all possible outcomes of…

Optimization and Control · Mathematics 2018-07-26 Jan Bok , Milan Hladík

We study the problem of partitioning a set of agents into coalitions based on the agents' additively separable preferences, which can also be viewed as a hedonic game. We apply three successively weaker solution concepts, namely…

Computer Science and Game Theory · Computer Science 2024-08-06 Michael McKay , Ágnes Cseh , David Manlove

This paper explores a PAC (probably approximately correct) learning model in cooperative games. Specifically, we are given $m$ random samples of coalitions and their values, taken from some unknown cooperative game; can we predict the…

Computer Science and Game Theory · Computer Science 2016-10-11 Maria-Florina Balcan , Ariel D. Procaccia , Yair Zick

In this paper we consider multi-agent coalitional games with uncertain value functions for which we establish distribution-free guarantees on the probability of allocation stability, i.e., agents do not have incentives to defect from the…

Optimization and Control · Mathematics 2022-06-24 George Pantazis , Filippo Fabiani , Filiberto Fele , Kostas Margellos

We conduct a computational analysis of fair and optimal partitions in additively separable hedonic games. We show that, for strict preferences, a Pareto optimal partition can be found in polynomial time while verifying whether a given…

Computer Science and Game Theory · Computer Science 2015-02-06 Haris Aziz , Felix Brandt , Hans Georg Seedig

We initiate the study of control in hedonic games, where an external actor influences coalition formation by adding or deleting agents. We consider three basic control goals (1) enforcing that an agent is not alone (NA); (2) enforcing that…

Computer Science and Game Theory · Computer Science 2026-02-24 Jiehua Chen , Jakob Guttmann , Merisa Mustajbašić , Sofia Simola

This work shows that the formation of a finite number of coalitions in a nonatomic network congestion game benefits everyone. At the equilibrium of the composite game played by coalitions and individuals, the average cost to each coalition…

Computer Science and Game Theory · Computer Science 2015-03-20 Cheng Wan

Partitioning a set of $n$ items or agents while maximizing the value of the partition is a fundamental algorithmic task. We study this problem in the specific setting of maximizing social welfare in additively separable hedonic games.…

Computer Science and Game Theory · Computer Science 2025-03-11 Martin Bullinger , Vaggos Chatziafratis , Parnian Shahkar

We propose a notion of a stable partition in a coalitional game that is parametrized by the concept of a defection function. This function assigns to each partition of the grand coalition a set of different coalition arrangements for a…

Computer Science and Game Theory · Computer Science 2007-05-23 Krzysztof R. Apt , Tadeusz Radzik

Knockout tournaments, also known as single-elimination or cup tournaments, are a popular form of sports competitions. In the standard probabilistic setting, for each pairing of players, one of the players wins the game with a certain (a…

Data Structures and Algorithms · Computer Science 2024-12-17 Juhi Chaudhary , Hendrik Molter , Meirav Zehavi

We introduce a class of strategic games in which agents are assigned to nodes of a topology graph and the utility of an agent depends on both the agent's inherent utilities for other agents as well as her distance from these agents on the…

Computer Science and Game Theory · Computer Science 2023-10-18 Martin Bullinger , Warut Suksompong

In this article, we study feature attributions of Machine Learning (ML) models originating from linear game values and coalitional values defined as operators on appropriate functional spaces. The main focus is on random games based on the…

Computer Science and Game Theory · Computer Science 2024-08-13 Alexey Miroshnikov , Konstandinos Kotsiopoulos , Khashayar Filom , Arjun Ravi Kannan

We show that computing an equilibrium in atomic splittable congestion games with player-specific affine cost functions $l_{e,i}(x) = a_{e,i} x + b_{e,i}$ is $\mathsf{PPAD}$-complete. To prove that the problem is contained in…

Computer Science and Game Theory · Computer Science 2020-01-20 Max Klimm , Philipp Warode

We analyse a coalition formation game between strategic service providers of a congestible service. The key novelty of our formulation is that it is a constant sum game, i.e., the total payoff across all service providers (or coalitions of…

Computer Science and Game Theory · Computer Science 2023-04-26 Shiksha Singhal , Veeraruna Kavitha , Jayakrishnan Nair

Federated learning is a distributed learning paradigm where multiple agents, each only with access to local data, jointly learn a global model. There has recently been an explosion of research aiming not only to improve the accuracy rates…

Computer Science and Game Theory · Computer Science 2021-06-18 Kate Donahue , Jon Kleinberg

We study coalition formation in the framework of fractional hedonic games (FHGs). The objective is to maximize social welfare in an online model where agents arrive one by one and must be assigned to coalitions immediately and irrevocably.…

Computer Science and Game Theory · Computer Science 2025-10-22 Martin Bullinger , René Romen , Alexander Schlenga

This paper considers a dynamic game with transferable utilities (TU), where the characteristic function is a continuous-time bounded mean ergodic process. A central planner interacts continuously over time with the players by choosing the…

Computer Science and Game Theory · Computer Science 2012-04-24 Dario Bauso , Puduru Viswanadha Reddy , Tamer Basar

Federated learning is a setting where agents, each with access to their own data source, combine models from local data to create a global model. If agents are drawing their data from different distributions, though, federated learning…

Computer Science and Game Theory · Computer Science 2020-12-18 Kate Donahue , Jon Kleinberg

In many multiagent environments, a designer has some, but limited control over the game being played. In this paper, we formalize this by considering incompletely specified games, in which some entries of the payoff matrices can be chosen…

Computer Science and Game Theory · Computer Science 2021-04-30 Markus Brill , Rupert Freeman , Vincent Conitzer