Recurrence theorems for topological Markov chains
- April 22 (Fri) at 17:00 - 19:00, 2022 (JST)
- Dr. Cédric Ho Thanh (Postdoctoral Researcher, Prediction Science Laboratory, RIKEN Cluster for Pioneering Research (CPR))
- Hybrid Format (Common Room 246-248 and Zoom) (Main Venue)
- Keita Mikami
Recurrence theorems place conditions under which probabilistic systems, specifically Markov chains, are expected to visit certain states infinitely often. For example, a printer with its many moving parts and the random requests it receives, may be described as a probabilistic system, and recurrence of the "ready to print" state is desirable. Recurrence theorems in the case of finite Markov chains are widely known.
In this talk, we are interested in generalization to the infinitary setting. As it turns out, some care has to be put in the definition of infinite Markov chains. Rather than simply infinite, the introduct topological Markov chains, and show how standard constructions can be naturally extended to thisframework: path spaces, cylinder sets, as well as the semantic of LTL and PCTL. With all these tools in hand, we finally state our recurrence theorems.
This is work in progress in collaboration with Natsuki Urabe and Ichiro Hasuo.
This seminar is hold in a hybrid style. If you want attend the seminar onsite, please contact to Keita Mikami.
This is a closed event for scientists. Non-scientists are not allowed to attend. If you are not a member or related person and would like to attend, please contact us using the inquiry form. Please note that the event organizer or speaker must authorize your request to attend.