1,982 research outputs found
Complexity of coalition structure generation
We revisit the coalition structure generation problem in which the goal is to
partition the players into exhaustive and disjoint coalitions so as to maximize
the social welfare. One of our key results is a general polynomial-time
algorithm to solve the problem for all coalitional games provided that player
types are known and the number of player types is bounded by a constant. As a
corollary, we obtain a polynomial-time algorithm to compute an optimal
partition for weighted voting games with a constant number of weight values and
for coalitional skill games with a constant number of skills. We also consider
well-studied and well-motivated coalitional games defined compactly on
combinatorial domains. For these games, we characterize the complexity of
computing an optimal coalition structure by presenting polynomial-time
algorithms, approximation algorithms, or NP-hardness and inapproximability
lower bounds.Comment: 17 page
Non-centralized Control for Flow-based Distribution Networks: A Game-theoretical Insight
This paper solves a data-driven control problem for a flow-based distribution network with two objectives: a resource allocation and a fair distribution of costs. These objectives represent both cooperation and competition directions. It is proposed a solution that combines either a centralized or distributed cooperative game approach using the Shapley value to determine
a proper partitioning of the system and a fair communication cost distribution. On the other hand, a decentralized noncooperative game approach computing the Nash equilibrium is used to achieve the control objective of the resource allocation under a non-complete information topology. Furthermore, an invariant-set property is presented and the closed-loop system stability is analyzed for the non cooperative game approach. Another contribution regarding the cooperative game approach is an alternative way to compute the Shapley value for the proposed specific characteristic function. Unlike the classical
cooperative-games approach, which has a limited application due to the combinatorial explosion issues, the alternative method allows calculating the Shapley value in polynomial time and hence can be applied to large-scale problems.Generalitat de Catalunya FI 2014Ministerio de Ciencia y Educación DPI2016-76493-C3-3-RMinisterio de Ciencia y Educación DPI2008-05818Proyecto europeo FP7-ICT DYMASO
Learning Cooperative Games
This paper explores a PAC (probably approximately correct) learning model in
cooperative games. Specifically, we are given random samples of coalitions
and their values, taken from some unknown cooperative game; can we predict the
values of unseen coalitions? We study the PAC learnability of several
well-known classes of cooperative games, such as network flow games, threshold
task games, and induced subgraph games. We also establish a novel connection
between PAC learnability and core stability: for games that are efficiently
learnable, it is possible to find payoff divisions that are likely to be stable
using a polynomial number of samples.Comment: accepted to IJCAI 201
Hierarchical Cooperation for Operator-Controlled Device-to-Device Communications: A Layered Coalitional Game Approach
Device-to-Device (D2D) communications, which allow direct communication among
mobile devices, have been proposed as an enabler of local services in 3GPP
LTE-Advanced (LTE-A) cellular networks. This work investigates a hierarchical
LTE-A network framework consisting of multiple D2D operators at the upper layer
and a group of devices at the lower layer. We propose a cooperative model that
allows the operators to improve their utility in terms of revenue by sharing
their devices, and the devices to improve their payoff in terms of end-to-end
throughput by collaboratively performing multi-path routing. To help
understanding the interaction among operators and devices, we present a
game-theoretic framework to model the cooperation behavior, and further, we
propose a layered coalitional game (LCG) to address the decision making
problems among them. Specifically, the cooperation of operators is modeled as
an overlapping coalition formation game (CFG) in a partition form, in which
operators should form a stable coalitional structure. Moreover, the cooperation
of devices is modeled as a coalitional graphical game (CGG), in which devices
establish links among each other to form a stable network structure for
multi-path routing.We adopt the extended recursive core, and Nash network, as
the stability concept for the proposed CFG and CGG, respectively. Numerical
results demonstrate that the proposed LCG yields notable gains compared to both
the non-cooperative case and a LCG variant and achieves good convergence speed.Comment: IEEE Wireless Communications and Networking Conference 201
Spectrum Leasing as an Incentive towards Uplink Macrocell and Femtocell Cooperation
The concept of femtocell access points underlaying existing communication
infrastructure has recently emerged as a key technology that can significantly
improve the coverage and performance of next-generation wireless networks. In
this paper, we propose a framework for macrocell-femtocell cooperation under a
closed access policy, in which a femtocell user may act as a relay for
macrocell users. In return, each cooperative macrocell user grants the
femtocell user a fraction of its superframe. We formulate a coalitional game
with macrocell and femtocell users being the players, which can take individual
and distributed decisions on whether to cooperate or not, while maximizing a
utility function that captures the cooperative gains, in terms of throughput
and delay.We show that the network can selforganize into a partition composed
of disjoint coalitions which constitutes the recursive core of the game
representing a key solution concept for coalition formation games in partition
form. Simulation results show that the proposed coalition formation algorithm
yields significant gains in terms of average rate per macrocell user, reaching
up to 239%, relative to the non-cooperative case. Moreover, the proposed
approach shows an improvement in terms of femtocell users' rate of up to 21%
when compared to the traditional closed access policy.Comment: 29 pages, 11 figures, accepted at the IEEE JSAC on Femtocell Network
MIMO-OFDM Based Energy Harvesting Cooperative Communications Using Coalitional Game Algorithm
This document is the Accepted Manuscript version. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In this paper, we consider the problem of cooperative communication between relays and base station in an advanced MIMO-OFDM framework, under the assumption that the relays are supplied by electric power drawn from energy harvesting (EH) sources. In particular, we focus on the relay selection, with the goal to guarantee the required performance in terms of capacity. In order to maximize the data throughput under the EH constraint, we model the transmission scheme as a non-transferable coalition formation game, with characteristic function based on an approximated capacity expression. Then, we introduce a powerful mathematical tool inherent to coalitional game theory, namely: the Shapley value (Sv) to provide a reliable solution concept to the game. The selected relays will form a virtual dynamically-configuredMIMO network that is able to transmit data to destination using efficient space-time coding techniques. Numerical results, obtained by simulating the EH-powered cooperativeMIMO-OFDMtransmission with Algebraic Space-Time Coding (ASTC), prove that the proposed coalitional game-based relay selection allows to achieve performance very close to that obtained by the same system operated by guaranteed power supply. The proposed methodology is finally compared with some recent related state-of-the-art techniques showing clear advantages in terms of link performance and goodput.Peer reviewe
The Cost of Stability in Coalitional Games
A key question in cooperative game theory is that of coalitional stability,
usually captured by the notion of the \emph{core}--the set of outcomes such
that no subgroup of players has an incentive to deviate. However, some
coalitional games have empty cores, and any outcome in such a game is unstable.
In this paper, we investigate the possibility of stabilizing a coalitional
game by using external payments. We consider a scenario where an external
party, which is interested in having the players work together, offers a
supplemental payment to the grand coalition (or, more generally, a particular
coalition structure). This payment is conditional on players not deviating from
their coalition(s). The sum of this payment plus the actual gains of the
coalition(s) may then be divided among the agents so as to promote stability.
We define the \emph{cost of stability (CoS)} as the minimal external payment
that stabilizes the game.
We provide general bounds on the cost of stability in several classes of
games, and explore its algorithmic properties. To develop a better intuition
for the concepts we introduce, we provide a detailed algorithmic study of the
cost of stability in weighted voting games, a simple but expressive class of
games which can model decision-making in political bodies, and cooperation in
multiagent settings. Finally, we extend our model and results to games with
coalition structures.Comment: 20 pages; will be presented at SAGT'0
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