Title: Communicating on Complex Networks: A Naming Game Model

It is a seminar of the Seminar Series on Complex Systems, Networks, Control And Applications [Link].

Chair: Dr Nelson Chan
Venue: Rm B6605 (Blue Zone), Academic 1, City University of Hong Kong
Date: 08 April 2016


Naming game simulates the process of naming an objective, forming a convention, learning new vocabulary and knowledge etc. by a population of agents organized in a certain communication network. By pair-wise iterative interactions, the population reaches consensus asymptotically. In this talk, first the concept of naming game and its applications, as well as some representative models are introduced. Second, two novel variants 1) naming game with learning errors in communications (NGLE), and 2) multi-word naming game (MWNG) are discussed. The NGLE studies the cases with communication errors during pair-wise conversations, with error rates in a uniform probability distribution. The MWNG simulates the naming game process when agents name an object by a sentence (i.e., a series of multiple words) for describing a complex object such as an opinion or an event. We employ three typical topologies used for the underlying communication network for both models, namely random-graph, small-world and scale-free networks. These new findings may help better understand the role of learning error, as well as the complicated negotiations and communications, and deepen our understanding of the human language development from a network science perspective. At the end, some challenges and potentially future work are introduced.

Relevant Papers:

1. Yang Lou and Guanrong Chen, "Analysis of the "Naming Game" with Learning Errors in Communications", Scientific Reports, 5, 12191; doi: 10.1038/srep12191 (2015) [Pdf] [Matlab Code] [SI] [BibTeX]
2. Yang Lou, Guanrong Chen, and Jianwei Hu, "Communicating with Sentences: A Multi-Word Naming Game Model", arXiv:1512.08347, (2015).


1. Flyer
2. The slides for presentation: Ppt/Pdf
3. Supplementary Materials for the relevant articles can be found from Prof Ron Chen's Webpage [Supplementary Materials 5 and 7]