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KI - Künstliche Intelligenz
Published in: KI - Künstliche Intelligenz 2-3/2018

11-05-2018 | Project Report

Design Space Exploration with Answer Set Programming

Authors: Christian Haubelt, Kai Neubauer, Torsten Schaub, Philipp Wanko

Published in: KI - Künstliche Intelligenz | Issue 2-3/2018

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Abstract

The aim of our project design space exploration with answer set programming is to develop a general framework based on Answer Set Programming (ASP) that finds valid solutions to the system design problem and simultaneously performs Design Space Exploration (DSE) to find the most favorable alternatives. We leverage recent developments in ASP solving that allow for tight integration of background theories to create a holistic framework for effective DSE.
previous article ASP for Conformance Analysis and Explanation of Clinical Guidelines Execution
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The Scientific journal "KI – Künstliche Intelligenz" is the official journal of the division for artificial intelligence within the "Gesellschaft für Informatik e.V." (GI) – the German Informatics Society - with constributions from troughout the field of artificial intelligence.

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Literature
1.
Gebser M, Kaminski R, Kaufmann B, Ostrowski M, Schaub T, Wanko P (2016) Theory solving made easy with clingo 5. In: Carro M, King A (eds) Technical communications of the thirty-second international conference on logic programming (ICLP’16), vol. 52. OASIcs, pp 2:1–2:15
2.
Janhunen T, Kaminski R, Ostrowski M, Schaub T, Schellhorn S, Wanko P (2017) Clingo goes linear constraints over reals and integers. Theory Pract Log Program 17(5–6):872–888MathSciNetCrossRefMATH
3.
Neubauer K, Haubelt C, Wanko P, Schaub T (2018) Systematic test case instance generation for the assessment of system-level design space exploration approaches. In: 21st workshop für Methoden und Beschreibungssprachen zur Modellierung und Verifikation von Schaltungen und Systemen (MBMV’18). To appear
4.
Neubauer K, Haubelt C, Wanko P, Schaub T (2018) Utilizing quad-trees for efficient design space exploration with partial assignment evaluation. In: Proceedings of the 23rd Asia and South Pacific design automation conference (ASP-DAC’18), pp 434–439. IEEE
5.
Neubauer K, Wanko P, Schaub T, Haubelt C (2017) Enhancing symbolic system synthesis through ASPmT with partial assignment evaluation. In: Proceedings of the 20th conference on design, automation and test in Europe (DATE’17), pp 306–309. IEEE
6.
Neubauer K, Wanko P, Schaub T, Haubelt C (2018) Exact multi-objective design space exploration using ASPmT. In: Proceedings of design, automation and test in Europe (DATE’18). To appear
7.
Pimentel A (2017) Exploring exploration: a utorial introduction to embedded systems design space exploration. IEEE Des Test 34(1):77–90CrossRef
8.
Romero J, Schaub T, Wanko P (2016) Computing diverse optimal stable models. In: Carro M, King A (eds) Technical communications of the thirty-second international conference on logic programming (ICLP’16), vol. 52. OASIcs, pp 3:1–3:14
Metadata
Title
Design Space Exploration with Answer Set Programming
Authors
Christian Haubelt
Kai Neubauer
Torsten Schaub
Philipp Wanko
Publication date
11-05-2018
Publisher
Springer Berlin Heidelberg
Published in
KI - Künstliche Intelligenz / Issue 2-3/2018
Print ISSN: 0933-1875
Electronic ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-018-0530-3

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