Project

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Games, Networks, and Society

English title Games, Networks, and Society
Applicant Tomassini Marco
Number 132802
Funding scheme Project funding (Div. I-III)
Research institution Département des systèmes d'information Faculté des Hautes Etudes Commerciales
Institution of higher education University of Lausanne - LA
Main discipline Information Technology
Start/End 01.01.2011 - 31.12.2012
Approved amount 107'149.00
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All Disciplines (2)

Discipline
Information Technology
Sociology

Keywords (6)

Cooperation; Networks; Games; Populations; Human behavior; Complex networks

Lay Summary (English)

Lead
This projects targets the theoretical and simulation modeling of structured populations of agents interacting according to strategic rulesrepresented by game theoretical concepts. To compare theoretical and actual behavior of human agents, we also employ behavioral experiments inthe laboratory.
Lay summary

Building on our research over the last five years and on the recent research of other groups, in this project we would like to advance the present knowledge about evolutionary games in social populations structured according to some complex network structure. Up to now only unweighted and mainly fixed networked populations have been investigated. In this project we have the intention to add more social realism both to the network of contacts as well as to the strategic decision processes of the agents forming the population. For the first part we will consider weighted networks both of fixed structure and dynamical ones in which weights, as well as strategies evolve in time and links may be severed or formed. In the second part we introduce experiments with human subjects, taking advantage of the ad hoc laboratory present in our Faculty  for that purpose. Finally, we would like to study more complex forms of interaction between agents as those that are represented by repeated games.

Direct link to Lay Summary Last update: 11.02.2013

Responsible applicant and co-applicants

Employees

Publications

Publication
Coordination on Networks: Does Topology Matter?
Antonioni Alberto, Cacault Maria Paula, Lalive Rafael, Tomassini Marco (2013), Coordination on Networks: Does Topology Matter?, in PLOS ONE, 8(2), e55033.
Cooperation on Social Networks and its Robustness
Antonioni Alberto, Tomassini Marco (2012), Cooperation on Social Networks and its Robustness, in Advances in Complex Systems, 15(1), 1250046.
Network Fluctuations Hinder Cooperation in Evolutionary Games
Antonioni Alberto, Tomassini Marco (2011), Network Fluctuations Hinder Cooperation in Evolutionary Games, in PLOS ONE, 6(10), e25555.
Coordination Games on Small-Worlds: Artificial Agents Vs. Experiments
Pestelacci Enea, Tomassini Marco, Antonioni Alberto (2011), Coordination Games on Small-Worlds: Artificial Agents Vs. Experiments, in Advances in Artificial Life, ECAL 2011, Paris.

Collaboration

Group / person Country
Types of collaboration
Université de Lausanne, HEC/DEEP Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
- Publication

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Complex Systems Summer School, "Pattern detection in complex systems" 02.07.2012 Paris
Swiss Doctoral School "Game Theory, Evolutionary Game Theory, and Learning in Games" 23.04.2012 Les Diablerets, Suisse
Advances in Artificial Life, ECAL 2011 08.08.2011 Paris, France
Lipari School for Scientific Research "Game-Theoretic Approach to Computational Complex Systems" 09.07.2011 Lipari, Italy


Associated projects

Number Title Start Funding scheme
143224 Games, Networks, and Society 01.01.2013 Project funding (Div. I-III)
119719 Evolutionary Games on Networks 01.06.2008 Project funding (Div. I-III)
111816 Evolutionary Games on Networks 01.06.2006 Project funding (Div. I-III)

Abstract

Building on our research over the last five years and on the recent research of other groups, we would like to advance the present knowledge about evolutionary games in social populations structuredaccording to some complex network structure. Up to now only unweighted and mainly fixed networked populations have been investigated. In this project we have the intention to add moresocial realism both to the network of contacts as well as to the strategic decision processes of the agents forming the population. For the first part we will consider weighted networks both of fixed structure and dynamical ones in which weights, as well as strategies evolve in time and links may be severed or formed. For the second part, we intend to use more advanced learning models that essentially come from computer science and that have not yet been commonly used in evolutionary games such as Q-learning. Finally, we would like to use all the pieces that have been put together in the above phases to study more complex forms of interaction between agents as those thatare represented by repeated games.
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