Pure bargaining problems with a coalition structure

The final publication is available at Springer via http://dx.doi.org/10.1007/s41412-016-0007-2We consider here pure bargaining problems endowed with a coalition structure such that each union is given its own utility. In this context we use the Shapley rule in order to assess the main options available to the agents: individual behavior, cooperative behavior, isolated unions behavior, and bargaining unions behavior. The latter two respectively recall the treatment given by Aumann–Drèze and Owen to cooperative games with a coalition structure. A numerical example illustrates the procedure. We provide criteria to compare any pair of behaviors for each agent, introduce and axiomatically characterize a modified Shapley rule, and determine its natural domain, that is, the set of problems where the bargaining unions behavior is the best option for all agents.Peer ReviewedPostprint (author's final draft

Efficient computation of the Shapley value for game-theoretic network centrality

The Shapley value—probably the most important normative payoff division scheme in coalitional games—has recently been advocated as a useful measure of centrality in networks. However, although this approach has a variety of real-world applications (including social and organisational networks, biological networks and communication networks), its computational properties have not been widely studied. To date, the only practicable approach to compute Shapley value-based centrality has been via Monte Carlo simulations which are computationally expensive and not guaranteed to give an exact answer. Against this background, this paper presents the first study of the computational aspects of the Shapley value for network centralities. Specifically, we develop exact analytical formulae for Shapley value-based centrality in both weighted and unweighted networks and develop efficient (polynomial time) and exact algorithms based on them. We empirically evaluate these algorithms on two real-life examples (an infrastructure network representing the topology of the Western States Power Grid and a collaboration network from the field of astrophysics) and demonstrate that they deliver significant speedups over the Monte Carlo approach. Fo

The axiomatic approach to three values in games with coalition structure

We study three values for transferable utility games with coalition structure, including the Owen coalitional value and two weighted versions with weights given by the size of the coalitions. We provide three axiomatic characterizations using the properties of Efficiency, Linearity, Independence of Null Coalitions, and Coordination, with two versions of Balanced Contributions inside a Coalition and Weighted Sharing in Unanimity Games, respectively.coalition structure; coalitional value

Computing the shapley value in allocation problems: Approximations and bounds, with an application to the Italian VQR research assessment program

In allocation problems, a given set of goods are assigned to agents in such a way that the social welfare is maximized, that is, the largest possible global worth is achieved. When goods are indivisible, it is possible to use money compensation to perform a fair allocation taking into account the actual contribution of all agents to the social welfare. Coalitional games provide a formal mathematical framework to model such problems, in particular the Shapley value is a solution concept widely used for assigning worths to agents in a fair way. Unfortunately, computing this value is a #P-hard problem, so that applying this good theoretical notion is often quite difficult in real-world problems. In this paper, we first review the application of the Shapley value to an allocation problem that models the evaluation of the Italian research structures with a procedure known as VQR. For large universities, the problem involves thousands of agents and goods (here, researchers and their research products). We then describe some useful properties that allow us to greatly simplify many such large instances. Moreover, we propose new algorithms for computing lower bounds and upper bounds of the Shapley value, which in some cases provide the exact result and that can be combined with approximation algorithms. The proposed techniques have been tested on large real-world instances of the VQR research evaluation problem

Computing the Shapley value in allocation problems: approximations and bounds, with an application to the Italian VQR research assessment program

In allocation problems, a given set of goods are assigned to agents in such a way that the social welfare is maximised, that is, the largest possible global worth is achieved. When goods are indivisible, it is possible to use money compensation to perform a fair allocation taking into account the actual contribution of all agents to the social welfare. Coalitional games provide a formal mathematical framework to model such problems, in particular the Shapley value is a solution concept widely used for assigning worths to agents in a fair way. Unfortunately, computing this value is a #P-hard problem, so that applying this good theoretical notion is often quite difficult in real-world problems. We describe useful properties that allow us to greatly simplify the instances of allocation problems, without affecting the Shapley value of any player. Moreover, we propose algorithms for computing lower bounds and upper bounds of the Shapley value, which in some cases provide the exact result and that can be combined with approximation algorithms. The proposed techniques have been implemented and tested on a real-world application of allocation problems, namely, the Italian research assessment program known as VQR (Verifica della Qualità della Ricerca, or Research Quality Assessment)1. For the large university considered in the experiments, the problem involves thousands of agents and goods (here, researchers and their research products). The algorithms described in the paper are able to compute the Shapley value for most of those agents, and to get a good approximation of the Shapley value for all of the

On the Shapley value and its application to the Italian VQR research assessment exercise

Research assessment exercises have now become common evaluation tools in a number of countries. These exercises have the goal of guiding merit-based public funds allocation, stimulating improvement of research productivity through competition and assessing the impact of adopted research support policies. One case in point is Italy's most recent research assessment effort, VQR 2011–2014 (Research Quality Evaluation), which, in addition to research institutions, also evaluated university departments, and individuals in some cases (i.e., recently hired research staff and members of PhD committees). However, the way an institution's score was divided, according to VQR rules, between its constituent departments or its staff members does not enjoy many desirable properties well known from coalitional game theory (e.g., budget balance, fairness, marginality). We propose, instead, an alternative score division rule that is based on the notion of Shapley value, a well known solution concept in coalitional game theory, which enjoys the desirable properties mentioned above. For a significant test case (namely, Sapienza University of Rome, the largest university in Italy), we present a detailed comparison of the scores obtained, for substructures and individuals, by applying the official VQR rules, with those resulting from Shapley value computations. We show that there are significant differences in the resulting scores, making room for improvements in the allocation rules used in research assessment exercises

POTENTIAL, VALUE AND PROBABILITY

This paper focuses on the probabilistic point of view and proposes a extremely simple probabilistic model that provides a single and simple story to account for several extensions of the Shapley value, as weighted Shapley values, semivalues, and weak (weighted or not) semivalues, and the Shapley value itself. Moreover, some of the most interesting conditions or notions that have been introduced in the search of alternatives to Shapley's seminal characterization, as 'balanced contributions' and the 'potential', are reinterpreted from this same point of view. In this new light these notions and some results lose their 'mystery' and acquire a clear and simple meaning. These illuminating reinterpretations strongly vindicate the complementariness of the probabilistic and the axiomatic approaches, and shed serious doubts about the achievements of the axiomatic approach since Nash's and Shapley's seminal papers in connection with the genuine notion of value.Coalition games, value, potential

An axiomatic approach to composite solutions

We investigate a situation in which gains from cooperation are represented by a cooperative TU-game and a solution proposes a division of coalitional worths. In addition, asymmetries among players outside the game are captured by a vector of exogenous weights. If a solution measures players' payoffs inherent in the game, and a coalition has formed, then the question is how to measure players' overall payoffs in that coalition. For this we introduce the notion of a composite solution. We provide an axiomatic characterization of a specific composite solution, in which exogenous weights enter in a proportional fashion.composite solution, external weights