Abstract
We introduce and characterize a new solution concept for TU games: The Surplus Distributor Prenucleolus. The new solution is a lexicographic value although it is not a weighted prenucleolus. The SD-prenucleolus satisfies core stability, strong aggregate monotonicity, null player out property in the class of balanced games and coalitional monotonicity in the class of monotonic games with veto players. We characterize the solution in terms of balanced collections of sets and we provide a simple formula for computing it in the class of monotonic games with veto players.
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Notes
In Sect. 3 we explain and interpret the new vector of satisfactions.
The definition of the prenucleolus does not allow this interpretation.
To our knowledge it is an open question whether there is any other continuous solution that satisfies these properties.
The same solution concept can be defined using the notion of excess instead of satisfaction. Given a game \((N,v)\) and an allocation \(x\), the excess of a coalition \(S\) with respect to \(x\) in game \((N,v)\) is defined as follows: \(e(S,x):=v(S)-x(S)\).
In Sect. 5 we provide a formula for computing the SD-prenucleolus of this game, i.e. \((3,2,2,1)\).
If \({\mathcal {H}}_{k}(x)={\mathcal {H}}_{k}(y)\) for any \(k>0\) then \({\mathcal {H}}_{k}(x)\) is balanced for any \(k>0\). If \(x\ne y\) then there exists \(k\) such that for all \(S\in {\mathcal {H}}_{k}(x), F(S,y)=F(S,x)\) and for all \(T\in {\mathcal {H}}_{k+1}(x)\backslash {\mathcal {H}}_{k}(x), F(T,y)>F(T,x)\). This implies that for all \(S\in {\mathcal {H}}_{k}(x), y(S)=x(S)\) and for all \( T\in {\mathcal {H}}_{k+1}(x)\backslash {\mathcal {H}}_{k}(x), y(T)>x(T)\). Since \({\mathcal {H}}_{k+1}(x)\) is balanced,
$$\begin{aligned} v(N)=x(N)=\sum \limits _{S\in {\mathcal {H}}_{k+1}(x)}\lambda _{S}x(S)<\sum \limits _{S\in {\mathcal {H}}_{k+1}(x)}\lambda _{S}y(S)=y(N)=v(N) \end{aligned}$$and we have a contradiction.
If a game with veto players is monotonic then it is balanced since the allocation where a veto player receives \(v(N)\) and the rest receive 0 is a core allocation.
References
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Acknowledgments
We thank two anonymous referees for their helpful comments and suggestions. J. Arin acknowledges the support of the Spanish Ministerio de Ciencia e Innovación under projects SEJ2012-31346 and ECO2009-11213, co-funded by the ERDF, and by Basque Government funding for Grupo Consolidado GIC07/146-IT-368-13.
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Appendix
Appendix
Proof of Lemma 3.
Proof
Assume that the lemma is not true. Consider the minimal number \(k\) such that there exist coalitions \(S,T\) with \(S\in {\mathcal {H}}_{k}, T\in {\mathcal {H}}_{k+1}\setminus {\mathcal {H}}_{k}\), and \(F(T)\le F(S)\). Consider the stage of the algorithm where the collection \({\mathcal {H}}_{k-1}\) is fixed. Since \(S\in {\mathcal {H}}_{k}\),
Note that \(F(T)=F_{{\mathcal {H}}_{k}}(T)\) since \(T\in {\mathcal {H}} _{k+1}\setminus {\mathcal {H}}_{k}\). The minimality of \(k\) implies that:
-
1.
For every \(i\in \sigma _{{\mathcal {H}}_{k-1}}(T)\) it holds that
$$\begin{aligned} f_{{\mathcal {H}}_{k},F}(i,T)=f_{{\mathcal {H}}_{k-1},F}(i,T)<F(S). \end{aligned}$$ -
2.
For every \(i\in \sigma _{{\mathcal {H}}_{k}}(T)\setminus \sigma _{{\mathcal {H}}_{k-1}}(T)\) it holds that
$$\begin{aligned} f_{{\mathcal {H}}_{k},F}(i,T)=F(S). \end{aligned}$$
We consider three cases:
-
1.
\(\sigma _{{\mathcal {H}}_{k}}(T)\ne T\). Since \(F_{{\mathcal {H}}_{k}}(T)=F(T)\le F(S)\), it holds that
$$\begin{aligned} F(S)&\ge F_{{\mathcal {H}}_{k}}(T)=\frac{x(T)-v(T)-\sum \nolimits _{i\in \sigma _{ {\mathcal {H}}_{k}}(T)}f_{{\mathcal {H}}_{k},F}(i,T)}{|T|-\left| \sigma _{{\mathcal {H}}_{k}}(T)\right| }\\&= \frac{x(T)-v(T)\!-\!\sum \nolimits _{i\in \sigma _{{\mathcal {H}}_{k-1}}(T)}f_{ {\mathcal {H}}_{k-1},F}(i,T)\!-\!F(S)\left( \left| \sigma _{{\mathcal {H}}_{k}}(T)\right| \!-\!\left| \sigma _{ {\mathcal {H}}_{k-1}}(T)\right| \right) }{|T|\!-\!\left| \sigma _{{\mathcal {H}}_{k}}(T)\right| } \end{aligned}$$This implies that
$$\begin{aligned} x(T)-v(T)-\sum \limits _{i\in \sigma _{{\mathcal {H}}_{k-1}}(T)}f_{{\mathcal {H}}_{k-1},F}(i,T)\le F(S)\left( \left| T\right| -\left| \sigma _{{\mathcal {H}}_{k-1}}(T)\right| \right) . \end{aligned}$$Therefore
$$\begin{aligned} \frac{x(T)-v(T)-\sum \nolimits _{i\in \sigma _{{\mathcal {H}}_{k-1}}(T)}f_{{\mathcal {H}}_{k-1},F}(i,T)}{\left| T\right| -\left| \sigma _{{\mathcal {H}}_{k-1}}(T)\right| }\le F(S) \end{aligned}$$and consequently \(F_{{\mathcal {H}}_{k-1}}(T)\le F(S)\) contradicting the fact that
$$\begin{aligned} F(S)=F_{{\mathcal {H}}_{k-1}}(S)=\min \limits _{U\not \in {\mathcal {H}}_{k-1}}F_{{\mathcal {H}}_{k-1}}(U). \end{aligned}$$Therefore \(F_{{\mathcal {H}}_{k-1}}(T)=\min \limits _{U\not \in {\mathcal {H}}_{k-1}}F_{{\mathcal {H}}_{k-1}}(U)\) and from Algorithm 1 it holds that \( T\in {\mathcal {H}}_{k}\) contradicting that \(T\in {\mathcal {H}}_{k+1}\setminus {\mathcal {H}}_{k}\).
-
2.
\(\sigma _{{\mathcal {H}}_{k-1}}(T)\ne T, \sigma _{{\mathcal {H}}_{k}}(T)=T\). Since \(\sigma _{{\mathcal {H}}_{k-1}}(T)\ne T\), it holds that
$$\begin{aligned} F_{{\mathcal {H}}_{k}}(T)&= x(T)-v(T)-\sum \limits _{i\in T}f_{{\mathcal {H}} _{k},F}(i,T)+\max \limits _{i\in T}f_{{\mathcal {H}}_{k},F}(i,T)\\&= x(T)-v(T)-\sum \limits _{i\in T}f_{{\mathcal {H}}_{k},F}(i,T)+F(S)\\&= x(T)-v(T)-\sum \limits _{i\in \sigma _{{\mathcal {H}}_{k-1}}(T)}f_{{\mathcal {H}} _{k-1},F}(i,T)-F(S)\left( \left| T\right| -\left| \sigma _{{\mathcal {H}}_{k-1}}(T)\right| \right) \\&\quad +F(S). \end{aligned}$$Since \(F_{{\mathcal {H}}_{k}}(T)=F(T)\le F(S)\), it can be obtained that
$$\begin{aligned} x(T)-v(T)-\sum \limits _{i\in \sigma _{{\mathcal {H}}_{k-1}}(T)}f_{{\mathcal {H}}_{k-1},F}(i,T)\le F(S)\left( \left| T\right| -\left| \sigma _{{\mathcal {H}}_{k-1}}(T)\right| \right) . \end{aligned}$$This implies that
$$\begin{aligned} \frac{x(T)-v(T)-\sum \nolimits _{i\in \sigma _{{\mathcal {H}}_{k-1}}(T)}f_{{\mathcal {H}}_{k-1},F}(i,T)}{\left| T\right| -\left| \sigma _{{\mathcal {H}}_{k-1}}(T)\right| }\le F(S). \end{aligned}$$Therefore, \(F_{{\mathcal {H}}_{k-1}}(T)\le F(S)\) and as in the previous case a contradiction is obtained.
-
3.
\(\sigma _{{\mathcal {H}}_{k-1}}(T)=\sigma _{{\mathcal {H}}_{k}}(T)=T\). Then
$$\begin{aligned} F_{{\mathcal {H}}_{k-1}}(T)=F_{{\mathcal {H}}_{k}}(T) \end{aligned}$$Since \(T\not \in {\mathcal {H}}_{k}\), it can be concluded that
$$\begin{aligned} F_{{\mathcal {H}}_{k}}(T)=F_{{\mathcal {H}}_{k-1}}(T)>\min \limits _{U\not \in {\mathcal {H}}_{k-1}}F_{{\mathcal {H}}_{k-1}}(U)=F_{{\mathcal {H}}_{k-1}}(S). \end{aligned}$$
\(\square \)
Proof of Proposition 6.
Proof
Consider games \((N,v)\) and \((N,v_{A})\) where \(v_{A}(N)=v(N)+A|N|\) and \(v_{A}(S)=v(S)\) for \(S\ne N\). Let \(x\in X(N,v)\) and \(y\in X(N,v_{A})\) such that \(y_{i}=x_{i}+A\) for each \(i\in N\).
It is sufficient to show that if the following holds for some \(k\ge 0\)
-
1.
\(F(S,y)=F(S,x)+A\) for each \(S\in {\mathcal {H}}_{k}\)
-
2.
The collections \({\mathcal {H}}_{k}(y)\) and \({\mathcal {H}}_{k}(x)\) coincide
then the two statements hold also for \(k+1\) (for \(k=0\) it is evident). Note that for every \(T\subsetneq N, i\in \sigma _{{\mathcal {H}}_{k}}(T)\) it holds that
Consider a coalition \(T\subsetneq N\). We distinguish two cases:
-
1.
\(\sigma _{{\mathcal {H}}_{k}}(T)\ne T\). Then
$$\begin{aligned} F_{{\mathcal {H}}_{k}}(T,y)&= \frac{y(T)-v_{A}(T)-\sum \nolimits _{i\in \sigma _{ {\mathcal {H}}_{k}}(T)}f_{{\mathcal {H}}_{k},F}^{v_{A}}(i,T)}{\left| T\right| -\left| \sigma _{{\mathcal {H}}_{k}}(T)\right| }\\&= \frac{x(T)+A|T|-v(T)-\sum \nolimits _{i\in \sigma _{{\mathcal {H}}_{k}}(T)}f_{ {\mathcal {H}}_{k},F}^{v}(i,T)-A\left| \sigma _{{\mathcal {H}}_{k}}(T)\right| }{|T|-\left| \sigma _{ {\mathcal {H}}_{k}}(T)\right| }\\&= \frac{x(T)-v(T)-\sum \nolimits _{i\in \sigma _{{\mathcal {H}}_{k}}(T)}f_{{\mathcal {H}}_{k},F}^{v}(i,T)}{|T|-\left| \sigma _{{\mathcal {H}}_{k}}(T)\right| }+A=F_{{\mathcal {H}}_{k}}^{v}(T,x)+A \end{aligned}$$ -
2.
\(\sigma _{{\mathcal {H}}_{k}}(T)=T\) Then
$$\begin{aligned} F_{{\mathcal {H}}_{k}}^{v_{A}}(T,y)&= y(T)-v_{A}(T)-\sum \limits _{i\in T}f_{{\mathcal {H}}_{k},F}^{v_{A}}(i,T)+\max \limits _{i\in T}f_{{\mathcal {H}}_{k},F}^{v_{A}}(i,T)\\&= x(T)+A|T|-v(T)-\sum \limits _{i\in T}f_{{\mathcal {H}}_{k},F}^{v_{A}}(i,T)\\&\quad -A|T|+ \max \limits _{i\in T}f_{{\mathcal {H}}_{k},F}^{v_{A}}(i,T)+A\\&= x(T)-v(T)-\sum \limits _{i\in T}f_{{\mathcal {H}}_{k},F}^{v_{A}}(i,T)+\max \limits _{i\in T}f_{{\mathcal {H}}_{k},F}^{v_{A}}(i,T)\\&\quad +A=F_{{\mathcal {H}}_{k}}^{v}(T,x)+A. \end{aligned}$$In this way, for every coalition \(T\subsetneq N\) it holds that
$$\begin{aligned} F_{{\mathcal {H}}_{k}}^{v_{A}}(T,y)=F_{{\mathcal {H}}_{k}}^{v}(T,x)+A \end{aligned}$$and therefore collections \({\mathcal {H}}_{k+1}\) in both games (\((N,v_{A})\) and \((N,v))\) coincide.
\(\square \)
Proof of Proposition 8.
Proof
Consider a balanced game \((N,v)\) where \(i\in N\) is a null player. Let \(x\in C(N,v)\) be a core allocation. To prove the NPO property of the SD-prenucleolus it is sufficient to show that for every \(S\subset N\setminus \{i\}\)
It is immediately apparent that \(x_{i}=0\) and coalition \(\{i\}\) has the minimal satisfaction, which is 0. Therefore if \(P\in \underset{S\subset N\backslash \{i\}}{\arg \min } \frac{x(S)-v(S)}{\left| S\right| }\) then \(F(P,x)=F\left( P\cup \{i\},x\right) \).
Assume that for coalitions that obtain their satisfaction before step \(k\) it holds that \(F(S,x)=F(S\cup \{i\},x)\). We now prove that for step \(k\) and any coalition \(S\in {\mathcal {H}}_{k}, S\subset N\backslash \{i\}\) it also holds that
Note that
We consider two cases (relevant and completed coalitions):
-
1.
\(\sigma _{{\mathcal {H}}_{k}}\left( S\cup \{i\}\right) \ne S\cup \{i\}\). Then
$$\begin{aligned} F_{{\mathcal {H}}_{k}}(S\cup \{i\})&= \frac{x(S\cup \{i\})-v(S\cup \{i\})-\sum \nolimits _{j\in \sigma _{{\mathcal {H}}_{k}}\left( S\cup \{i\}\right) }f_{{{\mathcal {H}}_{k}},F}(j,S)}{|S|+1-\left| \sigma _{{\mathcal {H}}_{k}}(S\cup \{i\})\right| }\\&= \frac{x(S)-v(S)-\sum \limits _{j\in \sigma _{{\mathcal {H}}_{k}}(S)}f_{{{\mathcal {H}}_{k}},F}(j,S)}{|S|+1-\left| \sigma _{{\mathcal {H}}_{k}}(S)\right| -1}=F_{{\mathcal {H}}_{k}}(S). \end{aligned}$$ -
2.
\(\sigma _{{\mathcal {H}}_{k}}(S\cup \{i\})=S\cup \{i\}\). Then
$$\begin{aligned} F_{{\mathcal {H}}_{k}}\left( S\cup \{i\}\right)&= x\left( S\cup \{i\}\right) -v\left( S\cup \{i\}\right) \\&\quad -\sum \limits _{j\in S\cup \{i\}}f_{{{\mathcal {H}}_{k}},F}(j,S)+\max \limits _{j\in S\cup \{i\}}f_{{{\mathcal {H}}_{k}},F}(j,S\cup \{i\})\\&= x(S)-v(S)-\sum \limits _{j\in S}f_{{{\mathcal {H}}_{k}},F}(j,S)+\max \limits _{j \in S}f_{{{\mathcal {H}}_{k}},F}(j,S\cup \{i\}) \end{aligned}$$
In order to show that \(F_{{\mathcal {H}}_{k}}(S\cup \{i\})=F_{{\mathcal {H}}_{k}}(S)\) it suffices to check that
But
Since the fact (1) holds for \(k^{\prime }<k\), it can be concluded that \(F_{{\mathcal {H}}_{k}}(T)=F_{{\mathcal {H}}_{k}}(T\cup \{i\})\) for every \( T\in {{\mathcal {H}}_{k}}\). Therefore
This implies that
and the proposition has been proved.\(\square \)
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Arin, J., Katsev, I. The SD-prenucleolus for TU games. Math Meth Oper Res 80, 307–327 (2014). https://doi.org/10.1007/s00186-014-0482-9
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DOI: https://doi.org/10.1007/s00186-014-0482-9