Contents:
1. Introduction
2. Custom Installation
3. Getting Started
3.1 Basic Example
3.2 Using a different Solver
4. Running the Package in Parallel
4.1 General Procedure
4.2 Running the Cddmathlink libraries in Parallel
5. MATLink and MATtug (Matlab toolbox MatTuGames)
6. Documentation
7. Graphics
8. Acknowledgment
9. License
TuGames is a Mathematica package to determine and to check some
game properties of transferable utility games. It provides more
than 200 different functions to calculate, for instance, (pre-)kernel
elements, the (pre-)nucleolus, the modiclus, the modified and proper modified
pre-kernel, the Shapley value, Lorenz solution, Dutta-Ray solution,
excess payoffs, the tau-value, chi-value, Gately point, the vertices of a core, and much more.
Moreover, it verifies if the game is convex, average-convex or superadditive
just to mention some interesting game properties. It can be used in serial
as well as in parallel mode, and in conjunction with MATLink to build up a Matlab
connection to invoke the toolbox MatTuGames. This package is exclusively
dedicated to Mathematica version 12.x and higher, because TUG-3.0.0 is the first
version that is transcribed to the new collection of algorithms for solving convex problems
introduced in version 12. For Mathematica versions smaller than 12.0 one should use TUG-2.6.2.
This version remains compatible with the most recent Mathematica version as long as
ConstrainedMax/ConstrainedMin and LinearProgramming/DualLinearProgramming are supported by Wolfram Research,
otherwise one has to switch to TUG-3.0.0 or later. In this respect, the graphical
features should run on all platforms. As a highlight, a fast algorithm to seek for a
pre-kernel element is implemented in the updated package. This algorithm is described
in the book
The Pre-Kernel as a Tractable Solution for Cooperative Games
An Exercise in Algorithmic Game Theory
Series: Theory and Decision Library C, Vol. 45
Meinhardt, Holger Ingmar
2014, XXXIII, 242 p. 8 illus., 4 illus. in color
More information can be found here:
Moreover, we have included a new package called ParaTuGames to literally run the major commands of TuGames in parallel. Notice that this package has not passed its stage of development. Hence, the user should use it with care and for testing only.
In addition, note that these functions/interfaces had to be provided in a Global context
to call the parallel commands of Mathematica within a package. This design requires
that during a running session with ParaTuGames no other variables of Global context
should be defined to avoid name conflicts and wrong results. Though use only the
commands that start with the prefix Para, and which returns a description of how to
use it. To get an idea of its usage, invoke in the panel of the Documentation Center TUG
and click then on hyperlink "ParaTuGames Package" to open the file
TUG/Tutorials/ParaExpGamePers12 from the Documentation Center (cf. Section 6).
Finally, this package does not require the configuration procedure as under Section 4.
A modified version of the package CooperativeGames that has been developed by M. Carter to run properly with Mathematica 12.x and higher is enclosed. It must be mentioned in this place that some commands of TuGames require routines that have been provided by the package CooperativeGames. A description of the package CooperativeGames can be found in
Hal R. Varian, Economic and Financial Modeling with Mathematica,
Telos Springer Publisher,1993, Chapter 8.
Furthermore, if one is interested in computing the vertices of a core the Mathematica package VertexEnum written by K. Fukuda and I. Mizukoshi must also be installed on the computer. But note that this function is very slow in computing all vertices of a core even for modern computers. You can overcome these shortcomings of VertexEnum by installing the C-library Cddmathlink written by the same authors to perform the same computational task more efficiently. It can be found under
for various UNIX, MacOSX and for Window systems. The library is linked via MathLink with the Mathematica Kernel. Under Linux and Mathematica 11.3 we complied successfully the binaries using the following compiler flags
MLFLAGS = -lML64i4 -lpthread -lrt -luuid -ldl
See also our post at
to overcome possible pitfalls, which might occur during a compilation of the Cddmathlink binaries.
For Windows and MacOSX Operating Systems pre-build binaries are available under
Cddlibml Binary
This C-library is required to use the graphical features of the package. Notice that the functions that based on this library are activated. To deactivate them comment in the corresponding lines in the TuGames.m file (cf. Section 2).
In order to install the library, we recommend it to do so in the TUG directory tree.
We have provided several folders that should receive the Cddmathlink executables for
different Operating System ABIs. To retrieve your system ID execute in a Notebook
$SystemID
We have provided some executables for RHEL 7.5, RHEL 8.2, and MacOSX. Unfortunately, we are not experienced enough under Windows to provide any for those. Thus, we invite the community to fill that gap and to provide some.
In order check for Mathematica versions smaller than 12.1 the paths where you have to install the Cddmathlink library call the command
In[1]:= PacletInformation["TUG"]
Out[1]= {Name -> TUG, Version -> 3.1.4 BuildNumber -> , Qualifier -> , WolframVersion -> 12+,
SystemID -> All, Description -> A Mathematica Package for Cooperative Game Theory,
Category -> , Creator -> Holger Ingmar Meinhardt <[email protected]>,
Publisher -> , Support -> , Internal -> False, Location -> /home/kit/xxx/xxxx/.Mathematica/Paclets/Repository/TUG-3.1.4
Context -> {TUG`coop`, TUG`vertex`, TUG`}, Enabled -> True, Loading -> Manual}
To get the same information and beyond that under Mathematica version 12.1, it is required to execute
In[1]:= PacletObject["TUG"][All]
Out[1]= {"Name" -> "TUG", "Version" -> "3.1.4", "WolframVersion" -> "12+",
"Qualifier" -> "", "SystemID" -> All, "Description" -> "A Mathematica Package for Cooperative Game Theory",
"Category" -> Missing["NotAvailable"], "Keywords" -> Missing["NotAvailable"],
"UUID" -> Missing["NotAvailable"],
"Creator" ->
"Holger Ingmar Meinhardt <[email protected]>",
"URL" -> "https://github.com/himeinhardt/TuGames",
"Internal" -> False,
"Context" -> {"TUG`coop`", "TUG`vertex`", "TUG`"},
"Loading" -> Manual, "AutoUpdating" -> False, "Enabled" -> True,
"Location" -> "/home/kit/xxx/xxxx/.Mathematica/Paclets/Repository/TUG-3.1.4"}
or alternatively
Information[PacletObject["TUG"]]
Then open the directory for Mathematica versions smaller than 12.1 by
SystemOpen@Lookup[PacletInformation["TUG"], "Location"]
or for Mathematica version 12.1 one opens the directory via
SystemOpen@Lookup[PacletObject["TUG"][All], "Location"]
This returns the root directory of TUG, and shows you the three folders
cddmathlink, cddmathlink2 and cddmathlink2gmp that should receive the Cddmathlink
executables.
The author has tested the functions extensively under LINUX x86/64, HP-UX and AIX.
Furthermore, the package was also be installed and tested successfully under Windows XP
and MacOSX. For more recent Windows OS the author has no experience. But the
programming language of Mathematica is system independent, thus, there should no problems
occur on these operating systems to run the basic functions of the package.
Since Version 2.5.1 the package is distributed as a Paclet, which allows a custom installation. The latest version is TUG-3.1.4, which is only compatible for Mathematica version 12.0 or higher. This version is not any more usable for versions that are smaller than 12.0. Notice that TUG-2.6.2 is the latest version that is compatible with Mathematica versions smaller than 12.0, and will remain compatible with the most recent Mathematica version as long as ConstrainedMax/ConstrainedMin and LinearProgramming/DualLinearProgramming are supported by Wolfram Research, otherwise one has to update to TUG-3.0.0 or later. The installation of the package requires about 90 MB free hard-disk space, and the Mathematica version should not be smaller than 10 while installing Version TUG-2.6.2. For Mathematica versions smaller than Version 10, a manual installation is requested. In that case one has to follow the guidelines related to the associated operating system that can be found from the Mathematica documentation.
The simplest method is to install the Paclet directly from GitHub under Mathematica V12.0 or later while executing
ResourceFunction["GitHubInstall"]["himeinhardt", "TuGames"]
For smaller versions than 12.0 start Mathematica, open a notebook, and execute therein
PacletInstall["/full/Path/to/TUG-2.6.2.paclet"]
to install TUG-2.6.2 the last version compatible with a Mathematica version smaller than 12.0. That should return the value
Paclet[TUG, 2.6.2, <>]
to indicate a successful installation. Notice that
"/full/Path/to/TUG-2.6.2.paclet"
indicates the directory where the TUG-2.6.2.paclet is located at your hard-disk.
Alternatively, one can directly install the package from GitHub with the help of the Mathematica-Tools from
For doing so, install first the package paclet generator and installer while executing within a running Mathematica session the command
Get["https://raw.githubusercontent.com/b3m2a1/mathematica-tools/master/PackageDataPacletInstall.m"]
After that, the current version of TuGames can be installed while calling from your notebook
PDInstallPaclet["https://github.com/himeinhardt/TuGames"]
The drawback of the foregoing procedure is that Linux (MacOSX?) users have to change the access permissions of the Cddmathlink executables. Follow the instructions from Section 1 to locate the Cddmathlink executables on your system after installation. Then change the file permissions in the associated folders by
chmod 755 cddmathlink
chmod 755 cddmathlink2
chmod 755 cddmathlink2gmp
within a Linux console. After this procedure, your Cddmathlink executables are available on your computer.
In order to use the graphical features of the package, it is recommended to install the Cddmathlink executables in pre-defined folders as described in Section 1. This C-library must be compiled by yourself if the shipped executables are not binary compatible with your OS. Windows users should compile it with the help of Cygwin.
If you plan to install these libraries somewhere else, then insert the path to this library in the file TuGames.m after the line of
:Comments for Windows OS ends:
Notice that the C-library is not necessary to run the package, however, the graphical features are then disabled.
After these steps, the installation procedure is completed, and one can start a session while executing
Needs["TUG`"]
All this does not affect an older installation.
Finally, in order to see how to open the documentation and to run some example we refer the user to Section 6 below.
The forthcoming discussion assumes that you have properly installed the files mentioned above on your computer.
To start with the calculation, we have to load some packages in a first step. This can be done by the following commands.
In[1]:= Needs["TUG`"]
===================================================
Loading Package 'TuGames' for Unix
===================================================
TuGames V3.1.4 by Holger I. Meinhardt
Release Date: 03.06.2024
Program runs under Mathematica Version 12.0 or later
Version 12.x or higher is recommended
===================================================
===================================================
Package 'TuGames' loaded
===================================================
Let us consider a small three-person TU-game. For this purpose define first the player set
In[2]:= T={1,2,3};
and then the characteristic values through
In[3]:= clv={0,0,0,0,90,100,120,220};
These data are necessary to define the TU-game, which can be accomplished by
In[4]:= ExpGame = DefineGame[T,clv];
After that we are in position to impose some basic operations like
In[5]:= ConvexQ[ExpGame]
Out[5]= True
In[6]:= CoreQ[ExpGame]
Out[6]= True
In[7]:= AverageConvexQ[ExpGame]
Out[7]= True
In[8]:= GameMonotoneQ[ExpGame]
Out[8]= True
In[9]:= ker=Kernel[ExpGame]
170 230 260
Out[9]= {---, ---, ---}
3 3 3
In[10]:= shv=ShapleyValue[ExpGame]
Out[10]= {65, 75, 80}
In[11]:= nc=Nucleolus[ExpGame]
170 230 260
Out[11]= {---, ---, ---}
3 3 3
In[12]:= WeaklyBalancedCollectionQ[ExpGame,nc]
Out[12]= True
In[13]:= prn=PreNucleolus[ExpGame]
170 230 260
Out[13]= {---, ---, ---}
3 3 3
In[14]:= BalancedCollectionQ[ExpGame,prn]
Out[14]= True
In[15]:= prk=PreKernelSolution[ExpGame]
170 230 260
Out[15]= {---, ---, ---}
3 3 3
In[16]:= mnc=Modiclus[ExpGame]
220 220 220
Out[16]= {---, ---, ---}
3 3 3
In[17]:= IsModiclusQ[ExpGame,mnc]
Out[17]= True
Alternatively, one can also supply a different method to check the existence of the core or to find a (pre-)kernel element or the (pre-)nucleolus. This may be useful when one encounters numerical issues, the evaluation lasts too long or with the need to determine an additional (pre-)kernel element. Although, the latter case is not relevant for a three-person game, we nevertheless demonstrate its usage for the above example.
In[18]:= CoreQ[ExpGame,Method->RevisedSimplex]
Out[18]= True
In[19]:= ker=Kernel[ExpGame,CallMaximize->False,Method->CLP]
170 230 260
Out[19]= {---, ---, ---}
3 3 3
In[20]:= nc=Nucleolus[ExpGame,CallMaximize->False,Method->RevisedSimplex]
170 230 260
Out[20]= {---, ---, ---}
3 3 3
In[21]:= prn=PreNucleolus[ExpGame,CallMaximize->False,Method->{InteriorPoint, Tolerance->10^-8}]
1065164637 695287163 1514771007
Out[21]= {----------, ---------, ----------}
18797023 9068963 17478127
In[22]:= WeaklyBalancedCollectionQ[ExpGame,prn]
Out[22]= False
In[23]:= BalancedCollectionQ[ExpGame,prn]
Out[23]= False
In[24]:= prn=PreNucleolus[ExpGame,CallMaximize->False,Method->{InteriorPoint, Tolerance->10^-9}]
170 230 260
Out[24]= {---, ---, ---}
3 3 3
In[25]:= prk=PreKernelSolution[ExpGame,SolutionExact->False,Method->IPOPT]
FindMinimum::sdir: Search direction has become too small.
FindMinimum::sdir: Search direction has become too small.
170 230 260
Out[25]= {---, ---, ---}
3 3 3
In[26]:= mnc=Modiclus[ExpGame,Method->{InteriorPoint, Tolerance->10^-7}]
297599353 80924213 63785847
Out[26]= {---------, --------, --------}
4058173 1103512 869807
In[27]:= IsModiclusQ[ExpGame,mnc]
Out[27]= False
In[28]:= Modiclus[ExpGame,Method->{InteriorPoint, Tolerance->10^-8}]
220 220 220
Out[28]= {---, ---, ---}
3 3 3
Admissible methods for the presented commands CoreQ, Kernel, Nucleolus, PreNucleolus or Modiclus are: RevisedSimplex, CLP, GUROBI, MOSEK, or Automatic. The default setting is Automatic. This option must be used in connection with CallMaximize->False. One can even try Method->{InteriorPoint, Tolerance->10^-7} to get a more precise result whenever one encounters numerical issues. In contrast, admissible methods for the function PreKernelSolution are: Automatic, Newton, QuasiNewton, InteriorPoint, ConjugateGradient, Gradient, PrincipalAxis, LevenbergMarquardt, MOSEK, GUROBI or IPOPT. Here, one has in addition to set SolutionExact->False to change to the non-default setting.
For more information see TUG/Tutorials/GettingStarted from the Documentation Center (cf. Section 6).
In order to run the TuGames package in parallel, we recommend putting at least in the Kernel
init.m file a new variable called $ParaMode while setting its value to "False". For doing so, open
the init.m file under ~/.Mathematica/Kernel by your favorite editor. Windows and MacOSX users should
consult $UserBaseDirectory to find their personal init.m. Then copy the variable
below with its value at the end of your Kernel init.m file, that is,
# init.m
$ParaMode="False";
Now open a notebook to start a Mathematica session. In order to run a session in parallel at the least the following commands must be invoked from your notebook:
LaunchKernels[]; or LaunchKernels[8]; or any other number reflecting the number of cores you can address.
$KernelCount
Needs["TUG`coop`CooperativeGames`"];
Needs["TUG`TuGames`"];
Needs["TUG`TuGamesAux`"];
$ParaMode="True";
ParallelNeeds["TUG`coop`CooperativeGames`"];
ParallelNeeds["TUG`TuGames`"];
ParallelNeeds["TUG`TuGamesAux`"];
To be sure that everything is distributed correctly, we distribute the definitions of the packages to all SubKernels.
DistributeDefinitions["TUG`coop`CooperativeGames`*"];
Then define your game using Set[] rather than SetDelayed[], let us say ExpGame, and invoke in addition:
SetSharedVariable[ExpGame];
Moreover, if some of the Mathematica packages which are used by TuGames are located on a different folder, you probably have to invoke in addition
LaunchKernels[];
....
....
ParallelEvaluate[AppendTo[$Path,"/Path/to/the/required/Packages"]];
ParallelNeeds["TUG`coop`CooperativeGames`"];
ParallelNeeds["TUG`TuGames`"];
....
....
For more information have also a look on the notebook file TUG/Guides/TuGamesParallelMamaV11d3 from
the Documentation Center (cf. Section 6).
If you plan to run even the Cddmathlink libraries in parallel, you have to set an additional variable
to the already set variable $ParaMode in the Kernel init.m file. For doing so, open again the init.m
file under ~/.Mathematica/Kernel by an editor. Then copy the variable $NotebookMode below with its
assigned value at the end of your Kernel init.m file, that is,
# init.m
$ParaMode="False";
$NotebookMode="True";
Here, we assumed that most people want to use the parallel mode within a notebook. In case that you
mostly use Mathematica from the command line or even on a compute node, then set the value of
the variable $NotebookMode to "False".
In the second step open now a notebook and put to the above commands under 4.1 the additional commands
in between, hence
LaunchKernels[];
.....
.....
Needs["TuGames`"];
ParallelNeeds[$ParaMode="True"];
ParallelNeeds[$NotebookMode="True"];
ParallelNeeds["TUG`coop`CooperativeGames`"];
ParallelNeeds["TUG`TuGames`"];
.....
.....
SetSharedVariable[YourDefinedGame];
In case that you intend to run Cddmathlink libraries in parallel on a compute node or from the command line, then you have to put into your input file the following commands:
LaunchKernels[];
.....
.....
Needs["TuGames`"] ;
ParallelNeeds[$ParaMode="True"];
ParallelNeeds[$NotebookMode="False"];
ParallelNeeds["TUG`coop`CooperativeGames`"];
ParallelNeeds["TUG`TuGames`"];
.....
.....
SetSharedVariable[YourDefinedGame];
If you encounter problems with the Cddmathlink libraries in parallel, then the following site might also be helpful
Run External Program in Parallel
As an example, also consult the documentation TUG/Guides/TuGamesMovieParaModeV6 from the Documentation Center (cf. Section 6).
If you want to use MATtug it is necessary to install MATLink from
that allows to open a Matlab connection from a running Mathematica session in order to be able to use the Matlab toolbox MatTuGames that is available under
For more information consult TUG/Guides/MATtug from the Documentation Center (cf. Section 6).
Open the Mathematica Documentation Center, and enter into the panel just TUG or guide/InstalledAddOns,
or scroll down, and click at the end of the page at the right corner on the field Add-ons and Packages. This directs
you to the Documentation of the package from which several examples can be called up, or more detailed information
can be retrieved. From there, one has access to about 230 pages of documentation.
There are also some graphical capabilities available, which should work under all platforms whenever the Cddmathlink libraries are installed. Features are for instance: plotting the core and strong epsilon core skeleton together with the nucleolus, kernel and Shapley value up to four players.
As an example, we visualize the geometric properties of the kernel and nucleolus (enlarged red dot) in the animation below. The Shapley value is the enlarged blue dot, which is given as a reference point.
For running the animation, a reload may be needed.
Consult for more information TUG/Guides/TuGamesView2dV6 or TUG/Guides/TuGamesView3dV6 from the Documentation Center.
We are very thankful to Szabolcs Horvát for his helpful support, suggestion of improvements, and of his piece of advice to follow best practice of publicizing a Mathematica package that allows a custom installation for everyone. Moreover, we owe him some executables for MacOSX, which ship with this version.
The author acknowledges support by the state of Baden-Württemberg through bwHPC.
Of course, the usual disclaimer applies.
This project is licensed under the MIT License - see the LICENSE file for details or MIT
Holger I. Meinhardt Institute of Operations Research University of Karlsruhe (KIT) E-mail: Holger.Meinhardt ät wiwi.uni-karlsruhe.de holger.meinhardt ät partner.kit.edu