Community

walter Member since: Wednesday, February 22, 2012

Modeling of Social Phenomena, Graph Algorithms, Opinion and Information Dynamics

n.malleson Member since: Thursday, January 05, 2012

PhD - Geography, MsC - Informatics

My primary research interest is in developing spatial computer models of social phenomena and my focus, in particular, has been on crime simulation.

Jennifer Badham Member since: Tuesday, February 10, 2015 Full Member

I have a particular interest in the way in which social network structure influences dynamic processes operating over the netowrk, such as adoption of behaviour or spread of disease. More generally, I am interested in using complex systems methods to understand social phenomena.

Carole Adam Member since: Friday, February 03, 2017

PhD in Artificial Intelligence
  • Since 2010: Associate Professor in Artificial Intelligence at Grenoble-Alpes University. Topic: human behaviour modelling, with a particular focus on emotions, cognitive biases, and their interplay with decision-making; social simulations and serious games for raising awareness about natural disasters and sustainable development, or for increasing civil engagement in urban planning.
  • 2008-2010: postdoctoral research fellow at RMIT, Melbourne, Australia. Supervisor: Lin Padgham. Topic: interactive intelligent emotional toy.
  • 2007-2008: research engineer at Orange Labs, Lannion, France. Supervisor: Vincent Louis. Topic: institutional logic in JADE for agent-based B2B mediation.
  • 2007: PhD in AI from Toulouse University. Supervisors: Andreas Herzig and Dominique Longin. Topic: logical modelling of emotions in BDI for artificial agents.

Improving agent models and architectures for agent-based modelling and simulation applied to crisis management. In particular modelling of BDI agents, emotions, cognitive biases, social attachment, etc.

Designing serious games to increase awareness about climate change or natural disasters; to improve civil engagement in sustainable urban planning; to teach Artificial Intelligence to the general public; to explain social phenomena (voting procedures; sanitary policies; etc).

Xiaotian Wang Member since: Friday, March 28, 2014

PHD of Engineering in Modeling and Simulation, Proficiency in Agent-based Modeling

Social network analysis has an especially long tradition in the social science. In recent years, a dramatically increased visibility of SNA, however, is owed to statistical physicists. Among many, Barabasi-Albert model (BA model) has attracted particular attention because of its mathematical properties (i.e., obeying power-law distribution) and its appearance in a diverse range of social phenomena. BA model assumes that nodes with more links (i.e., “popular nodes”) are more likely to be connected when new nodes entered a system. However, significant deviations from BA model have been reported in many social networks. Although numerous variants of BA model are developed, they still share the key assumption that nodes with more links were more likely to be connected. I think this line of research is problematic since it assumes all nodes possess the same preference and overlooks the potential impacts of agent heterogeneity on network formation. When joining a real social network, people are not only driven by instrumental calculation of connecting with the popular, but also motivated by intrinsic affection of joining the like. The impact of this mixed preferential attachment is particularly consequential on formation of social networks. I propose an integrative agent-based model of heterogeneous attachment encompassing both instrumental calculation and intrinsic similarity. Particularly, it emphasizes the way in which agent heterogeneity affects social network formation. This integrative approach can strongly advance our understanding about the formation of various networks.

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