TY  - JOUR
A1  - Gebser, Martin
A1  - Kaminski, Roland
A1  - Schaub, Torsten H.
T1  - Complex optimization in answer set programming
JF  - Theory and practice of logic programming
N2  - Preference handling and optimization are indispensable means for addressing nontrivial applications in Answer Set Programming (ASP). However, their implementation becomes difficult whenever they bring about a significant increase in computational complexity. As a consequence, existing ASP systems do not offer complex optimization capacities, supporting, for instance, inclusion-based minimization or Pareto efficiency. Rather, such complex criteria are typically addressed by resorting to dedicated modeling techniques, like saturation. Unlike the ease of common ASP modeling, however, these techniques are rather involved and hardly usable by ASP laymen. We address this problem by developing a general implementation technique by means of meta-prpogramming, thus reusing existing ASP systems to capture various forms of qualitative preferences among answer sets. In this way, complex preferences and optimization capacities become readily available for ASP applications.
KW  - Answer Set Programming
KW  - Preference Handling
KW  - Complex optimization
KW  - Meta-Programming
Y1  - 2011
U6  - https://doi.org/10.1017/S1471068411000329
SN  - 1471-0684
VL  - 11
IS  - 3
SP  - 821
EP  - 839
PB  - Cambridge Univ. Press
CY  - New York
ER  - 
TY  - THES
A1  - Kaminski, Roland
T1  - Complex reasoning with answer set programming
N2  - Answer Set Programming (ASP) allows us to address knowledge-intensive search and optimization problems in a declarative way due to its integrated modeling, grounding, and solving workflow. A problem is modeled using a rule based language and then grounded and solved. Solving results in a set of stable models that correspond to solutions of the modeled problem. In this thesis, we present the design and implementation of the clingo system---perhaps, the most
widely used ASP system. It features a rich modeling language originating from the field of knowledge representation and reasoning, efficient grounding algorithms based on database evaluation techniques, and high performance solving algorithms based on Boolean satisfiability (SAT) solving technology.
The contributions of this thesis lie in the design of the modeling language, the design and implementation of the grounding algorithms, and the design and implementation of an Application Programmable Interface (API) facilitating the use of ASP in real world applications and the implementation of complex forms of reasoning beyond the traditional ASP workflow.
KW  - Answer Set Programming
KW  - Declarative Problem Solving
KW  - Grounding Theory
KW  - Preference Handling
KW  - Answer Set Solving modulo Theories
KW  - Temporal Answer Set Solving
Y1  - 2023
ER  -