Tag Archives: Markov processes

13/11/2018 – Talk by prof. Dieter Fiems

Title:  Modelling group dynamics in epidemic opinion propagation
Time: 13:00
Location: Meeting Room B, Building Zeta
Type: Research talk
Speaker:  Dieter Fiems
Abstract:  Motivated by weblogs and discussion forums, epidemic opinion propagation on affiliation networks is investigated. An affiliation network is a bi-partite graph describing the connections between individuals and their affiliations. In contrast to epidemics on complex networks, the epidemic spreading process in the current setting is not the consequence of pairwise interactions among individuals but of a group dynamic. We derive a Markov model for the epidemic process and its fluid limit obtained by sending the population size to infinity while keeping the number of affiliations constant. This results in a set of modified SIR-like ordinary differential equations. Different types of group dynamics are studied numerically and the accuracy of the fluid limit is verified by simulation.

14/09/2016 – Talk by prof. Jia Yuan Yu (Concordia Institute of Information System Engineering)

Title: Central-Limit Approach to Risk-aware Markov Decision Processes
Time: 14:00
Location: Meeting room
Type: Research Result
Speaker: Jia Yuan Yu
Abstract: Whereas classical Markov decision processes maximize the expected reward, we consider minimizing the risk. We propose to evaluate the risk associated to a given policy over a long-enough time horizon with the help of a central limit theorem. The proposed approach works whether the transition probabilities are known or not. We also provide a gradient-based policy improvement algorithm that converges to a local optimum of the risk objective.