GRASP Student Seminar Series: Spring 2006

April 12, 5:00 PM, 307 Levine Hall

Abstract: The main idea of abstracting dynamical systems is, given a dynamical system, we construct a relatively simpler system that is, in some sense, equivalent to the original. Simpler system usually means a system that can be analyzed with less computing effort. The equivalence between the original system and its abstraction guarantees that the result of the computation performed on the abstraction can be carried over into the original system.

In this talk, I present a relaxed notion of abstraction for a class of stochastic systems, where the abstraction is only required to be approximately equal to the original system. This is done by introducing the concept of stochastic bisimulation function, with which we can measure the distance between the systems and hence the quality of the abstraction. For the class of systems concerned, the construction of such functions leads to a tractable computational problem.

Biography: A. Agung Julius is a postdoctoral researcher in the Department of Electrical and Systems Engineering at the University of Pennsylvania. Agung's research interests include mathematical systems theory, behavioral systems and control theory, interplay between theoretical computer science and systems theory, hybrid systems, reduction of complex systems, verification of complex systems, and stochastic models in systems biology.


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