Session details
Date: Apr 8, 2025
Series: GuestStream #101.1
Guests: Mohsen Jafari, Yulin Li
Questa pagina è stata tradotta automaticamente dall'inglese. Visualizza l'originale in inglese.
GuestStream #101.1
Apr 8, 2025 · with Mohsen Jafari, Yulin Li
▶ Watch on YouTube ↗Date: Apr 8, 2025
Series: GuestStream #101.1
Guests: Mohsen Jafari, Yulin Li
Transcript
The full transcript is available on GitHub. This excerpt is generated by automated speech recognition and may contain errors.
All right. Hello and welcome. It is April 8th, 2025, and we're on active guest stream 101.1 with Nosan Jafari and Yuli Lee. So thank you both for joining and looking forward to this presentation and discussion. Well, Daniel, thank you so much for having us here. It's really great pleasure. What I'm going to do is I'll have, I have few slides for you. I'll present my slides and it's an open discussion. So please stop me whenever you have questions. And that's about it. So let me start. Again, my name is Nosan Jafari. I am professor at Rutgers University of Engineering. This work, we have been working in this area for the last, I would say four to five years. And this is a joint work with Professor Andrea Mata from Polytechnical Milano. There are four PhD students currently working on this. Actually, one of them, Yu Fei Hong, the last one, he graduated about a year ago. But the rest are in the program. They are working in the program. So what I'm going to do, well, again, it took us a while to understand active influencing. I am myself coming from automation background. I have computer science, half engineering. So I'm very familiar with the modeling, with the stochastic systems and so on and so forth. But definitely, in terms of active influencing, it was a little bit different for me to get acquainted with. But that's why it took a while to basically understand the terms, the jargons and the underlying assumptions and so on. But we feel that we are quite comfortable with the theory and the framework. Dr. Dr. Dr. Dr. Dr. Dr. Dr. community i'm sure many of us have heard about this where you have some buildings each building has zones and and then you have the community which has many buildings in it and these communities are part of a larger network sometimes called distribution network if you are looking at from energy perspective then you can connect to the power grid or any other type of network so they're different you know there's a hierarchy of hierarchy of different layers in the system and it's quite complex it's the way that information is being and passed up and down and being processed there are many issues in terms of privacy confidentiality abstraction of abstraction of information and so on so that's one example and i'm going to talk more about this as we move on another example is in the top in the production systems the production systems manufacturing systems are usually complex systems there are many many stations robotics and you name it and in in there are many examples where you have hundreds or thousands of this machinery in the same same uh you know same uh area and of course these systems interact with the environment with outside and there are lots of complex interactions inside the system another system of the same complexity that involves again machinery and human is is roadways you know navigation in the roadways you have cars and and these days we have mixed traffic you have smart cars you have not so smart cars and and of course the interaction between all this you know vehicles in the system uh in terms of navigation is a quite complex problem um along the same line you can look at the simpler systems but you can look at very complex dynamics in the system i'm borrowing this picture from from the literature but basically think about this table with a robot that tries to push the ball but the table has a complex dynamics in terms of tilting in terms of friction on the table so exactly what you do and what you see may not be exactly what you are trying to do and this is another type of system that we are we are trying to to look into and study and again if time allows we will discuss this let me just go back a little bit uh the whole idea of looking at degenerative modeling is not new for us uh i would say uh about 15 to 20 years ago i i have i i did some work in this in this topic again for large complex systems the whole problem there is that to build this uh like in this case this automata models…