# Design Space Exploration via Answer Set Programming Modulo Theories

## TL;DR

This paper introduces a novel methodology combining Answer Set Programming with background theories to enable direct multi-objective optimization of non-linear objectives in embedded system design, facilitating complex design space exploration.

## Contribution

It presents the first integration of multi-objective optimization of non-linear objectives into ASP for embedded system design, enhancing expressiveness and solution diversity.

## Key findings

- Enables direct optimization of non-linear objectives in ASP
- Supports diverse solution sets with desirable properties
- Demonstrates effectiveness in complex embedded system design problems

## Abstract

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.