Baja cave paintingModelling Social Interaction in Information Systems (MSIIS)

Lectures: 14 lectures, every Wednesday 18:00-19:30 between 3/9/14 and 3/12/14
Location: Irinyi 218, University of Szeged.
Lecturer: Dr David Hales ( e-mail

Course Overview

Computer systems are increasingly distributed. Networks link nodes that serve users and carry out computations. Collectively, system level properties emerge rather than being planned. This is similar to how human and animal societies operate. In human societies individual goals and behaviours through interaction generate collective properties such as norms, laws, markets and government. These properties structure and shape our world. In animal societies evolved behaviours can solve complex optimisation problems through individual rule following as evidenced by the social insects (ants, bees and termites).

Recent innovations such as Bittorrent and Bitcoin show how algorithms developed with reference to social, economic and biological theory can change not only the computational networks but also society in general.

In this course we will study both theoretical concepts about social interaction and case studies of successfully deployed systems that embody them. We will also critically consider a set of techniques used to understand and research social interaction such as:
We will also study pioneers in the area such as John Von Neumann, Herbert Simon, John Holland, Robert Axelrod and others.

We will critically discuss what good models are and how to go about constructing them. We will also consider some of the historical theories of social systems as they relate to information systems.

Prerequisites: The course assumes some programming ability but no specific computer language will be mandated. It is also assumed that students will be open to ideas traditionally outside of computer science such as social science and economics but no prior knowledge will be assumed of these areas.

There will be no formal exam. MSc students will be assessed through a scientific paper reading in which they choose and read a paper of interest and then present the main ideas from the paper to the group. In addition to the paper reading PhD students will be assessed through a simple programming assignment. Specific details about the assessment process can be found here: MSIIS-Assessment.pdf

(the course aims to):
Objectives (by the end of the course students will be able to):


Below are listed each lecture sessions and links to related materials. Papers and books listed in the slides can be found in the books and papers sections below the lectures section.

1. Introduction and Overview: Aims and objectives of the course; Overview of different kinds of modelling and different kinds of social interaction; Outline of some general concepts such as complexity, emergence, self-organisation, decentralisation power and control. Software NetLogo, Golly. Slides1.pdf
[date: 3/9/2014]

2. Cellular Automata: History of CA’s their motivations and interpretations; Examples of 1D and 2D CA’s. People: John von Neumann, Stephen Wolfram, John Conway, Chris Langdon. Examples: game of life, different 1D CA’s; ideas of chaos; Idea of Turing complete CA. Software: NetLogo/Life & 1D CA's, Golly. slides2.pdf
[date: 10/9/2014]

3. Schelling's Segregation Model: A more detailed look at the segregation model (shown in lecture 1). Exploring the behaviour of the model systematically. How results from the model have been applied to design of a P2P clustering algorithm. Software: NetLogo/Segregation model. People: Thomas Schelling. slides3.pdf
[date: 17/9/2014]

4. Evolution of cooperation: Problem of cooperation in general and how it relates to social systems. Some concepts from game theory. Presentation of the Prisoners’ Dilemma game. Detailed look at Axelrod's computer tournaments. People Axelrod. slides4.pdf
[date: 24/9/2014]

5. Bittorrent and cooperation: Overview of Bittorrent file-sharing protocol; How the protocol relates to cooperation theory; People: Bram Cohen. Software: Bittorrent. slides5.pdf
[date: 1/10/2014]

6. Social Welfare and Bittorrent credit dynamics: Idea of a social welfare function; some simple examples and the people and ideas that inform them. Rawls' veil of ignorance. Credit dynamics in a bittorrent private community (BitCrunch model). People: Bentham, Pareto, Rawls, Sen. slides6.pdf
[date 8/10/2014]

7) Agent-based modelling (and mutli-agent systems): What is agent-based modelling? Examples of agent-based modelling; Different kinds of agents – reactive, adaptive, cognitive. How ABM relates to MAS. ABM platforms / languages. Different kinds of model. The Sugarscape ABM. slides7.pdf
[date: 15/10/2014]

8. Evolution, co-evolution (and artificial life): Evolutionary algorithms, genetic algorithms, co-evolutionary systems, interaction structures other than mean-field, concept of an ESS, evolving cooperation on a cellular automata, endogenous reproduction, artificial life, cultural evolution, evolving interaction structures - dynamic networks of evolving cooperation. People: Tom Ray, Nowak & May, Dawkins, John Holland. slides8.pdf
[date: 22/10/2014]

9. Bitcoin and other applications. (Guest lecture: Dr Victor Greshenko, Citrea LLC, Moscow, Russian Federation). Interesting comment on Bitcoin from 2011. Victor give the following links that reference things mentioned in his talk: Victor's swarmjs project Hawala Ripple Lada Adamic [social network researcher] Wikipedia as ant-hill Livejournal as ant-hill
[date: 29/10/2014]

10. Markets (and Money): What is a market? Textbook supply / demand and equilibrium. Real markets. Macro and micro models. Continuous Double Auction electronic markets, ZIP (zero-intelligence-plus) algorithmic trader agents. Non-equilibrium models, speculation, contagion, El Farol Bar,  SFI artificial stock market. Prediction markets. Money - what is it (why don't I have any)? Modern money, central banks and local banks. Theories of value. New P2P money. People: Dave Cliff, Brian Arthur, Keynes, Hayek, Alan Kirman, Satoshi Nakamoto. slides10.pdf
[date: 5/11/2014]

11. Application of socio-economic ideas to the design of distributed systems. (Guest lecture: Dr Rameez Rahman, EPFL, Lausanne, Swiss). See his blog here. Recent and relevant PhD thesis here. Interesting blog post about ABM and Tolstoy. slides11.pdf. The following papers were referenced in the talk (and are listed below in the papers section) How to cheat bittorrent, Effort-based incentives, Design Space Analysis. Note also this blog post on big data and this cartoon on big data which relate to the debate we had at the end of the lecture.
[date: 12/11/2014]

12. Student paper reading assignments. Students each give 10 to 15 mins presentation plus 5 mins questions on their chosen paper (max 5 slides if they decide to use slides). A link to the pdf of the slides and paper is given here. Also most of the papers are listed in the paper section:
[date: 19/11/2014]

13. Cognitive Agent Modelling; The reasons and motivation for cognitive agent modelling; BDI modelling; AgentSpeak language; (Guest lecture, Dr Mario Paulucci, CNR Rome & University of Bologna, Italy). The mindmap of presentation can be found here.This contains significantly more material than there was time cover in the lecture. Also see a recent paper related to gossip, reputation and cooperation here. Mario is also co-author of an entire book on reputation in artificial societies. Details and review of book here.
[date: 26/11/2014]

14. Student paper reading assignments. Students each give 10 to 15 mins presentation plus 5 mins questions on their chosen paper (max 5 slides if they decide to use slides). A link to the pdf of the slides and paper is given here. Also most of the papers are listed in the paper section:
[date: 3/12/2014]

Support Materials

You do not have to read, use or watch all these things. I will discuss in the lectures what you might wish to look at. Hence they a provided as background that allow you explore a topic mentioned in the lectures that you are interested in.


Papers / Articles




Blog posts