Strategic information transmission with receiver's type-dependent decision sets, by Stephan Sémirat (GAEL, Grenoble)
– February 27, 2020
Strategic information transmission with receiver's type-dependent decision sets.
Abstract:
We consider a sender-receiver game, in which the sender has finitely many types and the receiver makes decisions in a bounded real interval. We assume that utility functions are concave, single-peaked and supermodular. After the cheap talk phase, the receiver makes a decision, which must fulfill a constraint (e.g., a participation constraint) that depends on the sender's type. Hence a necessary equilibrium condition is that the receiver maximizes his expected utility subject to the constraints of all positive probability types. This necessary condition may not hold at the receiver's prior belief, so that a non-revealing equilibrium may fail to exist. We propose a constructive algorithm that always achieves a partitional perfect Bayesian equilibrium
Title : Ranking Online Social Users by their Influence
Abstract:
In this talk I will introduce an original mathematical model to analyse the diffusion of posts within a generic online social platform. As a main result, using the developed model, we derive in closed form the probabilities that posts originating from a given user are found on the Wall and Newsfeed of any other inside the platform. By combining these probabilities we get a measure of per user influence on the entire network. This constitutes a new centrality measure which is more expressive than existing ones, in the sense that it combines the user position on the graph with the user posting activity. Comparisons with simulations show the accuracy of this model and its robustness with respect to the modelling assumptions. Furthermore, its application on large data traces from real platforms asserts its validity for real world applications, and the possibilities it opens for explaining real diffusion phenomena and predicting actual user influence.
Bio:
Anastasios Giovanidis received the Diploma degree in electrical and computer engineering from the National Technical University of Athens, Greece, in 2005, and the Dr. Ing. degree in wireless communications and information theory from the Technical University of Berlin, Germany, in 2010. He has been a postdoctoral fellow, first with the Zuse Institute Berlin, Germany (with Prof. Martin Grötschel), and later with INRIA, Paris, France (with Prof. François Baccelli). Since 2013 he is a permanent researcher of the French National Center for Scientific Research (CNRS, CR1). From 2013 until 2016 he was affiliated with the Télécom ParisTech CNRS-LTCI laboratory. Since 2016 he is affiliated with the computer science laboratory LIP6 of the Sorbonne University. He has served as the General co-chair for WIOPT 2017, CCDWN 2018, and GameNets 2019. His current research interests include performance analysis and optimisation of telecom and social networks, supported by data analysis and learning.
F. Falniowski: "Robust routes to chaos in congestion games: The effects of scale on learning dynamics"
– March 13, 2020
We study the effects of increasing the population size/scale of costs in congestion games and generalize recent results for the well known Multiplicative Weights Update dynamic to a large class of Follow-the-Regularized Leader dynamics (FoReL). We prove that even in simple linear congestion games with two parallel links as the population/scale increases, learning becomes unstable and (unless the game is fully symmetric) eventually Li-Yorke chaotic. Despite their chaotic instability, the dynamics provably converge in a time-average sense to an exact equilibrium for any choice of learning rate and any scale of costs.
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