Design Space Exploration via Answer Set Programming Modulo Theories
This addresses system-level design challenges for embedded systems in mobile devices and cars, representing a novel methodological advancement.
The paper tackles the complex design problem of embedded systems by developing a declarative methodology using Answer Set Programming with background theories, achieving the first direct integration of multi-objective optimization of non-linear objectives into ASP.
The design of embedded systems, that are ubiquitously used in mobile devices and cars, is becoming continuously more complex such that efficient system-level design methods are becoming crucial. My research aims at developing systems that help the designer express the complex design problem in a declarative way and explore the design space to obtain divers sets of solutions with desirable properties. To that end, we employ knowledge representation and reasoning capabilities of ASP in combination with background theories. As a result, for the first time, we proposed a sophisticated methodology that allows for the direct integration of multi-objective optimization of non-linear objectives into ASP. This includes unique results of diverse sub-problems covered in several publications which I will present in this work.