The proportional coalitional Shapley value

We propose a modification of the Shapley value for monotonic games with a coalition structure. The resulting coalitional value is a twofold extension of the Shapley value in the following sense: (1) the amount obtained by any union coincides with the Shapley value of the union in the quotient game; and (2) the players of the union share this amount proportionally to their Shapley value in the original game (i.e., without unions). We provide axiomatic characterizations of this value close to those existing in the literature for the Owen value and include applications to coalition formation in bankruptcy and voting problems.     

Simplification of Shapley value for cooperative games via minimum carrier

Shapley value is one of the most fundamental concepts in cooperative games. This paper investigates the calculation of the Shapley value for cooperative games and establishes a new formula via carrier. Firstly, a necessary and sufficient condition is presented for the verification of carrier, based on which an algorithm is worked out to find the unique minimum carrier. Secondly, by virtue of the properties of minimum carrier, it is proved that the profit allocated to dummy players (players which do not belong to the minimum carrier) is zero, and the profit allocated to players in minimum carrier is only determined by the minimum carrier. Then, a new formula of the Shapley value is presented, which greatly reduces the computational complexity of the original formula, and shows that the Shapley value only depends on the minimum carrier. Finally, based on the semi-tensor product (STP) of matrices, the obtained new formula is converted into an equivalent algebraic form, which makes the new formula convenient for calculation via MATLAB.     

The Shapley and Banzhaf values in microarray games

We provide a characterization of the Banzhaf value on the class of the microarray games, and another characterization of the Shapley value, on the same class, in the spirit of [Moretti S, Patrone F, Bonassi S. The class of microarray games and the relevance index for genes. TOP 2007;15:256–80]. Then we compare the results given by the two indices when applied to a colon tumor data-set published in literature.     

Soft cooperation systems and games

A cooperative game for a set of agents establishes a fair allocation of the profit obtained for their cooperation. In order to obtain this allocation, a characteristic function is known. It establishes the profit of each coalition of agents if this coalition decides to act alone. Originally players are considered symmetric and then the allocation only depends on the characteristic function; this paper is about cooperative games with an asymmetric set of agents. We introduced cooperative games with a soft set of agents which explains those parameters determining the asymmetry among them in the cooperation. Now the characteristic function is defined not over the coalitions but over the soft coalitions, namely the profit depends not only on the formed coalition but also on the attributes considered for the players in the coalition. The best known of the allocation rules for cooperative games is the Shapley value. We propose a Shapley kind solution for soft games.     

基于动态模糊联盟合作博弈的区间模糊Shapley值

利用模糊数学相关理论,针对n人合作博弈中支付函数是模糊三角函数的情形,对经典Shapley值提出的三条公理进行了拓展,并构造了区间模糊Shapley值。考虑到盟友在合作结束后需要对具体的联盟收益进行分配,利用构造的区间模糊Shapley值隶属函数给出了确定的收益分配方案。最后利用实例对该方法的有效性和可行性进行了说明。     

模糊动态联盟收益分配改进算法

动态联盟注重盟员间的合作,在参与人合作过程中,收益分配是其理性选择的结果。实际生活中收益又具有模糊性,所以应用模糊合作博弈来研究该问题非常必要。这里的关键问题是模糊合作博弈Shapley值的求解问题。将模糊合作博弈中的模糊支付用模糊结构元表示,给出基于结构元理论的各局中人Shapley值求解方法,使其得到解析表达。求解该方法可以体现出决策者不同行为偏好下动态收益的不同分配,应用结果验证了改进算法的有效性。     

模糊合作对策区间Shapley值法的改进及应用

模糊合作对策的收益分配是个复杂问题,受到合作方的风险承担、合作努力、市场竞争、创新贡献和资源投入等因素的影响,而且不同因素有着不同的重要性。运用区间Shapley值法对模糊合作对策的收益进行初步分配。通过将AHP-GEM法和模糊综合评价法相结合,引入收益分配的综合修正因子,对区间Shapley值法进行改进,建立了模糊合作对策利益分配的改进模型。以制造业和物流业联盟为例,说明了改进模型的实用性和可行性。     

An overview of recent applications of Game Theory to bioinformatics

The goal of this work is to provide a comprehensive review of different Game Theory applications that have been recently used to predict the behavior of non-rational agents in interaction situations arising from computational biology.In the first part of the paper, we focus on evolutionary games and their application to modelling the evolution of virulence. Here, the notion of Evolutionary Stable Strategy (ESS) plays an important role in modelling mutation mechanisms, whereas selection mechanisms are explained by means of the concept of replicator dynamics.In the second part, we describe a couple of applications concerning cooperative games in coalitional form, namely microarray games and Multi-perturbation Shapley value Analysis (MSA), for the analysis of genetic data. In both of the approaches, the Shapley value is used to assess the power of genes in complex regulatory pathways.     

A linear approximation method for the Shapley value

The Shapley value is a key solution concept for coalitional games in general and voting games in particular. Its main advantage is that it provides a unique and fair solution, but its main drawback is the complexity of computing it (e.g., for voting games this complexity is #p-complete). However, given the importance of the Shapley value and voting games, a number of approximation methods have been developed to overcome this complexity. Among these, Owen's multi-linear extension method is the most time efficient, being linear in the number of players. Now, in addition to speed, the other key criterion for an approximation algorithm is its approximation error. On this dimension, the multi-linear extension method is less impressive. Against this background, this paper presents a new approximation algorithm, based on randomization, for computing the Shapley value of voting games. This method has time complexity linear in the number of players, but has an approximation error that is, on average, lower than Owen's. In addition to this comparative study, we empirically evaluate the error for our method and show how the different parameters of the voting game affect it. Specifically, we show the following effects. First, as the number of players in a voting game increases, the average percentage error decreases. Second, as the quota increases, the average percentage error decreases. Third, the error is different for players with different weights; players with weight closer to the mean weight have a lower error than those with weight further away. We then extend our approximation to the more general k-majority voting games and show that, for n players, the method has time complexity O(k²n) and the upper bound on its approximation error is .     

Polynomial calculation of the Shapley value based on sampling

In this paper we develop a polynomial method based on sampling theory that can be used to estimate the Shapley value (or any semivalue) for cooperative games. Besides analyzing the complexity problem, we examine some desirable statistical properties of the proposed approach and provide some computational results.     

要素双重模糊下的合作博弈Shapley值的算法

考虑到现实应用中,局中人可能以不同的参与度参加到不同的联盟中,并且他们在合作之前不确定不同合作策略选择下的收益,则在传统合作博弈中应用模糊数学理论。基于Choquet积分,将支付函数和参与度拓展为模糊数,给出要素双重模糊下的模糊合作博弈的定义和模糊合作博弈Shapley值的定义。应用模糊结构元理论,构造了要素双重模糊下的模糊合作博弈的Shapley值,使模糊Shapley值的隶属函数得到解析表达。通过一个算例,来说明该模型的具体应用。可以看出,该研究方法和结论易掌握、推广,使模糊合作博弈理论可以更广泛地应用到现实生活中。     

Two-stage network games

In the paper, two-stage network games are studied. At the first stage of the game, the players form a network, while at the second stage they choose strategies according to the network realized at the first stage. Both noncooperative and cooperative settings are considered. In the noncooperative case, the Nash equilibrium is used as a solution concept, whereas the cooperative setting involves an allocation (the Shapley value) as a solution concept. It is demonstrated that the Shapley value does not satisfy the time consistency property.     

Reduced game property of the Egalitarian Non-k-Averaged Contribution (EN k AC-) value and the Shapley value

The Egalitarian Non- k -Averaged Contribution (EN ^k AC-) value for TU-game represents the equal division of the surplus of the total profits, given that each player is already allocated his individual contribution specified by worths of coalitions of size k . This paper deals with the axiomatic characterization of the EN ^k AC-value on the class of cooperative games with a fixed player set as well as a variable player set. The latter axiomatization involves a consistency axiom in terms of the reduced games. The EN ^k AC-value is the unique value on the class of cooperative games with a variable player set which possesses the relative invariance under strategic equivalence, the equal treatment property and the reduced game property for two types of reduced games. We also propose a new reduced game in terms of which the Shapley value is axiomatized.     

Cooperative network design: A Nash bargaining solution approach

The Network Design problem has received increasing attention in recent years. Previous works have addressed this problem considering almost exclusively networks designed by selfish users, which can be consistently suboptimal. This paper addresses the network design issue using cooperative game theory, which permits to study ways to enforce and sustain cooperation among users. Both the Nash bargaining solution and the Shapley value are widely applicable concepts for solving these games. However, the Shapley value presents several drawbacks in this context.For this reason, we solve the cooperative network design game using the Nash bargaining solution (NBS) concept. More specifically, we extend the NBS approach to the case of multiple players and give an explicit expression for users’ cost allocations. We further provide a distributed algorithm for computing the Nash bargaining solution. Then, we compare the NBS to the Shapley value and the Nash equilibrium solution in several network scenarios, including real ISP topologies, showing its advantages and appealing properties in terms of cost allocation to users and computation time to obtain the solution.Numerical results demonstrate that the proposed Nash bargaining solution approach permits to allocate costs fairly to users in a reasonable computation time, thus representing a very effective framework for the design of efficient and stable networks.     

Cooperative games with multiple attributes

ABSTRACT

In this paper, we introduce the notion of a cooperative game with multiple attributes where players can provide partial participations in multiple attributes and form coalitions. The power or influence of the players due to their multiple attributes is evaluated based on their memberships in the coalitions. Our game therefore, extends the notion of cooperative games with fuzzy coalitions. The Shapley function for this class of games is proposed as a rational and fair solution concept. Every fuzzy game stems out of a specific crisp game under the assumption that the players provide partial memberships in forming multiple coalitions simultaneously. We adopt similar techniques to obtain the cooperative games with multiple attributes from their crisp counterparts and subsequently determine their Shapley functions.     

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

Abstract

In allocation problems with indivisible goods, money compensation is used to distribute worth in a fair way. Coalitional games provide a formal mathematical framework to model such problems, and the Shapley value is a solution concept widely used to realise a fair distribution. To overcome its intractability, we describe how to simplify allocation problems and we propose algorithms for computing lower bounds and upper bounds of the Shapley value 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.     

Parallel characterizations of a generalized Shapley value and a generalized Banzhaf value for cooperative games with level structure of cooperation

We present parallel characterizations of two different values in the framework of restricted cooperation games. The restrictions are introduced as a finite sequence of partitions defined on the player set, each of them being coarser than the previous one, hence forming a structure of different levels of a priori unions. On the one hand, we consider a value first introduced in Ref. [18], which extends the Shapley value to games with different levels of a priori unions. On the other hand, we introduce another solution for the same type of games, which extends the Banzhaf value in the same manner. We characterize these two values using logically comparable properties.     

具有交流结构的区间模糊联盟合作对策

当前具有模糊联盟的合作对策研究主要基于任意局中人可自由结盟的基本假设,但现实结盟活动中,局中人普遍受到资源或地位等因素的限制,其合作往往具有交流结构限制。因此,基于Choquet模糊延拓研究了具有交流结构的区间模糊多人合作对策,给出了相应区间模糊联盟平均树解,并通过公理化体系对此解进行了研究。通过供应链纵向合作创新收益分配实例应用,并与区间模糊联盟合作对策的Shapley值进行比较,说明该方法的现实有效性。     

Statistical analysis of the Shapley value for microarray games

Game theory may be helpful to analyze the relevance of genes in determining a specific biological condition or response of interest (e.g. a disease of interest) in a population of cells.The first goal of this paper is to understand how accurate is the relevance index provided by the Shapley value on games arising from microarray experiments. Such a question is the prelude to the second subject of this paper, which concerns comparison between the relevance indices under different biological conditions.     

Ranking efficient DMUs using cooperative game theory

The problem of ranking Decision Making Units (DMUs) in Data Envelopment Analysis (DEA) has been widely studied in the literature. Some of the proposed approaches use cooperative game theory as a tool to perform the ranking. In this paper, we use the Shapley value of two different cooperative games in which the players are the efficient DMUs and the characteristic function represents the increase in the discriminant power of DEA contributed by each efficient DMU. The idea is that if the efficient DMUs are not included in the modified reference sample then the efficiency score of some inefficient DMUs would be higher. The characteristic function represents, therefore, the change in the efficiency scores of the inefficient DMUs that occurs when a given coalition of efficient units is dropped from the sample. Alternatively, the characteristic function of the cooperative game can be defined as the change in the efficiency scores of the inefficient DMUs that occurs when a given coalition of efficient DMUs are the only efficient DMUs that are included in the sample. Since the two cooperative games proposed are dual games, their corresponding Shapley value coincide and thus lead to the same ranking. The more an efficient DMU impacts the shape of the efficient frontier, the higher the increase in the efficiency scores of the inefficient DMUs its removal brings about and, hence, the higher its contribution to the overall discriminant power of the method. The proposed approach is illustrated on a number of datasets from the literature and compared with existing methods.