Tag Archive: Opinion Dynamics

May 22

Tutorial OOP(II): One problem, different possible classes

additional resources
agent paper: Sobkowicz
source-code: AgentTutorials
Arxiv: Full Tutorial

In the previous tutorial, we saw how to tackle an opinion dynamics problem using agents as a class in an Object Oriented Programming (OOP) approach. In many topics of interest in (socio-)physics and chemistry, we deal with a large number of particles, be it electrons, atoms, agents, stars, … These are contained in a superstructure (electrons⇒atom, atoms⇒molecule/solid, agents⇒population, stars⇒galaxy,…) which is generally represented in the code as an array. As we noted in the previous tutorial, there were several variables which were global to the agents, but we implemented them as properties of the agents anyhow. As a result, a significant amount of additional memory needed to be allocated for storing in essence the same data. This was done to prevent the need of having to provide this information at every function call.

Returning to our problem of interest, we now consider two object classes: The TAgent-class and the TPopulation-class. This leads to several possible ways this problem can be implemented.

  1. Array of TAgents: As was done in the previous tutorial, we only make a class of the agents, and put them in an array.
  2. TPopulation of TAgents: In this case we construct a class called TPopulation of which one property is the set of TAgents. The TPopulation-class also contains some of the global variables as properties, and operations on this set are methods of the TPopulation-class.
  3. TPopulation-class without TAgent-class: In this last case, the agents are dissolved, and their properties are stored in array-properties of the TPopulation-class. The methods of the TAgent-class now become methods of the TPopulation-class. And the global variables become additional properties of the TPopulation-class.

Although the true OOP-programmer may only consider the  second option the way to go, we will consider the third option in this tutorial.

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May 03

Tutorial OOP(I): Objects in Fortran 2003

After having set up our new project in the first session of this tutorial, we now come to an important second step: choosing and creating our Objects. In OOP, the central focus is not a (primitive) variable or a function, but “an object”. In Object Oriented Programming (OOP) most if not all variables and functions are incorporated in one or more (types of) objects. An object, is just like a real-life object; It has properties and can do things. For example: a car. It has properties (color, automatic or stick, weight, number of seats,…) and can do things (drive, break down, accelerate,…). In OOP, the variables containing the values that give the color, weight, stick or not,… of the car are called the properties of the car-object. The functions that perform the necessary calculations/modifications of the variables to perform the actions of driving, breaking down,… are called the methods.

Since we are still focusing on the opinion dynamics paper of Sobkowicz, let us use the objects of that paper to continue our tutorial. A simplified version of the research question in the paper could be as follows:

How does the (average) opinion of a population of agents evolve over time?

For our object-based approach, this already contains much of the information we need. It tells us what our “objects” could be: agents. It gives us properties for these objects: opinion. And it also tells us something of the methods that will be involved: opinion…evolve over time.

Let us now put this into Fortran code. A class definition in Fortran uses the TYPE keyword, just like complex data types.

  1. Type, public :: TAgentClass
  2. private
  3. real :: oi !< opinion
  4. contains
  5. private
  6. procedure, pass(this), public :: getOpinion
  7. procedure, pass(this), public :: setOpinion
  8. procedure, pass(this), public :: updateOpinion
  9. end type TAgentClass

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Apr 26

Tutorial: Starting a new Object Oriented Fortran-project in Code::Blocks

Because Fortran has been around since the time of the dinosaurs, or so it seems, one persistent myth is that modern constructs and techniques are not supported. One very important modern programming approach is Object Oriented Programming (OOP). Where procedural programming focuses on splitting the program in smaller functional units (functions and procedures), OOP is centered on “Objects and Classes”. These objects, just like real life objects, have properties (eg. name, color, position, …) and contain methods (i.e. procedures representing their functionality). This sounds more complex than it actually is. In a very simplistic sense, objects and classes are created by extending complex data types in procedural programming languages with internally contained functions/procedures, referred to as methods. In the table below, you see a limited comparison between the two. The first three languages are procedural oriented languages, while the last two allow for OOP.

C Pascal F95 C++ OOP F2003 OOP
data type keyword struct record type class type
containing variables field field field property property
containing functions / / / method method
inheritance no no no yes yes

In this tutorial series, I want to show how you can use OOP in Fortran in scientific codes. As a first example, I will show you how to create an agent based opinion dynamics code implementing the model presented by Sobkowicz in a publication I recently had  to review.

I choose this as our tutorial example (over for example geometric shapes) because it is a real-life scientific example which is simple enough to allow for several aspects in scientific and OO-programming to be shown. In addition, from the physicists point of view: particle or agent, it is all the same to us when we are implementing their behavior into a program.(You could even start thinking in terms of NPC’s for a game, although game-dynamics in general require quite a bit more implementation)

So let us get started. First, you might wish to grab a copy of the paper by Sobkowicz (it’s freely accessible), just to be able to more easily track the notation I will be using in the code. After having installed code::blocks it is rather straight-forward to create a new Fortran program.

  1. Open code::blocks, and start a new project (File > New > Project) by selecting “Fortran application”newProject
  2. Provide a “Project title” and a location to store the files of the new project.setupProject1
  3. Choose your compiler (GNU Fortran Compiler, make sure this is the one selected) and Finish.setupProject2
  4. Now Code::Blocks will present you a new project, with already one file present: main.f90 HelloWorld
  5. First we are going to rename this main file, e.g. to main.f95, to indicate that we will be  using Fortran 95 code in this file. By right-clicking on the file name (indicated with the red arrow) you see a list of possible op w this option while the file is open in the right-hand pane. Close the file there, and now you can rename main.f95.
  6. Although we will be following the OOP paradigm for the main internal workings of our program, a procedural setup will be used to set up the global lines of the program. I split the code in three levels: The top-level being the main program loop which is limited to the code below, the middle level which contains what you may normally consider the program layout (which you can easily merge with the top level) and the bottom level which contains the OO innards of our program. All subroutines/functions belonging to the middle level will be placed in one external module (Tutorial1) which is linked to the main program through the use-statement at line 2 and the single subroutine call (RunTutorial1).
  1. program AgentTutorials
  2. use Tutorial1;
  3. implicit none
  4.  
  5. write(*,'(A)') "Welcome to the Agents OOP-Fortran Tutorial"
  6. call RunTutorial1()
  7. write(*,'(A)') "-- Goodbye"
  8. end program AgentTutorials
  1. Next step, we need a place for the RunTutorial1 subroutine, and all other subroutines/functions that will provide the global layout of our agents-program. Make a new file in Code::Blocks as followsNewFile
  2. and select a Fortran source file and finish by placing it in a directory of your choice and click OK.NewFile2
  3. In this empty file, a module is setup in the following fashion:
  1. module Tutorial1
  2. implicit none
  3. private
  4.  
  5. public :: RunTutorial1
  6.  
  7. contains
  8. !+++++++++++++++++++++++++++++++++++++
  9. !>\brief Main program routine for the first agents tutorial
  10. !!
  11. !! This is the only function accessable outside this module.
  12. !<------------------------------------
  13. subroutine RunTutorial1()
  14. write(*,'(A)') "----Starting Turorial 1 subprogram.----"
  15. write(*,'(A)') "-------End Turorial 1 subprogram.------"
  16. end subroutine RunTutorial1
  17.  
  18. end module Tutorial1
  1. implicit none : Makes sure that you have to define all variables.
  2. private : The private statement on line 3 makes sure that everything inside the module remains hidden for the outside world, unless you explicitly make it visible. In addition to data/information-hiding this also helps you keep your namespace in check.
  3. public :: Runtutorial1 : Only the function Runtutorial1 is available outside this module.(Because we want to use it in program  AgentTutorials.)
  4. contains : Below this  keyword all functions and subroutines of the module will be placed.
  5. “!” : The exclamation marks indicate a comment block. In this case it is formatted to be parsed by doxygen.
  6. subroutine XXX  / end subroutine XXX : The subroutine we will be implementing/using as the main loop of our agents program. Note that in recent incarnations of fortran the name of the subroutine/function/module/… is repeated at their end statement. For small functions this may look ridiculous, but for larger subroutines it improves readability.

At this point or program doesn’t do that much, we have only set up the framework in which we will be working. Compiling and running the program (F9 or Build > Build and run) should show you:

AgentsRun1 In the next session of this tutorial we will use OO-Fortran 2003 to create the agent-class and create a first small simulation.

 

 

Oct 28

Rationality: A Social-Epistemology Perspective

Authors: Sylvia Wenmackers, Danny E. P. Vanpoucke, and Igor Douven
Journal: Front. Psychol. 5, 581 (2014)
doi: 10.3389/fpsyg.2014.00581
IF(2014): 2.560
export: bibtex
pdf: <Front.Psychol.> (open Access)

Abstract

Both in philosophy and in psychology, human rationality has traditionally been studied from an ‘individualistic’ perspective. Recently, social epistemologists have drawn attention to the fact that epistemic interactions among agents also give rise to important questions concerning rationality. In previous work, we have used a formal model to assess the risk that a particular type of social-epistemic interactions lead agents with initially consistent belief states into inconsistent belief states. Here, we continue this work by investigating the dynamics to which these interactions may give rise in the population as a whole.