Equivalence between answer-set programs under (partially) fixed input
Answer Set Programming has become an increasingly popular formalism for declarative problem solving. Among the huge body of theoretical results, investigations of different equivalence notions between logic programs play a fundamental role for understanding modularity and optimization. While strong...
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| Published in | Annals of mathematics and artificial intelligence Vol. 83; no. 3-4; pp. 277 - 295 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
Cham
Springer International Publishing
01.08.2018
Springer Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1012-2443 1573-7470 1573-7470 |
| DOI | 10.1007/s10472-017-9567-5 |
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| Abstract | Answer Set Programming has become an increasingly popular formalism for declarative problem solving. Among the huge body of theoretical results, investigations of different equivalence notions between logic programs play a fundamental role for understanding modularity and optimization. While strong equivalence between two programs holds if they can be faithfully replaced by each other in any context (facts and rules), uniform equivalence amounts to equivalent behavior of programs under any set of facts. Both notions (as well as several variants thereof) have been extensively studied. However, the somewhat reverse notion of equivalence which holds if two programs are equivalent under the addition of any set of proper rules (i.e., all rules except facts) has not been investigated yet. In this paper, we close this gap and give a thorough study of this notion, which we call rule equivalence , and its parameterized version where we allow facts over a given restricted alphabet to appear in the context. This notion of equivalence is thus a relationship between two programs whose input is (partially) fixed but where additional proper rules might still be added. Such a notion might be helpful in debugging of programs. We give full characterization results and a complexity analysis for the propositional case of rule equivalence and its relativized versions. Moreover, we address the problem of program simplification under rule equivalence. Finally, we show that rule equivalence is decidable in the non-ground case. |
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| AbstractList | Answer Set Programming has become an increasingly popular formalism for declarative problem solving. Among the huge body of theoretical results, investigations of different equivalence notions between logic programs play a fundamental role for understanding modularity and optimization. While strong equivalence between two programs holds if they can be faithfully replaced by each other in any context (facts and rules), uniform equivalence amounts to equivalent behavior of programs under any set of facts. Both notions (as well as several variants thereof) have been extensively studied. However, the somewhat reverse notion of equivalence which holds if two programs are equivalent under the addition of any set of proper rules (i.e., all rules except facts) has not been investigated yet. In this paper, we close this gap and give a thorough study of this notion, which we call rule equivalence , and its parameterized version where we allow facts over a given restricted alphabet to appear in the context. This notion of equivalence is thus a relationship between two programs whose input is (partially) fixed but where additional proper rules might still be added. Such a notion might be helpful in debugging of programs. We give full characterization results and a complexity analysis for the propositional case of rule equivalence and its relativized versions. Moreover, we address the problem of program simplification under rule equivalence. Finally, we show that rule equivalence is decidable in the non-ground case. Answer Set Programming has become an increasingly popular formalism for declarative problem solving. Among the huge body of theoretical results, investigations of different equivalence notions between logic programs play a fundamental role for understanding modularity and optimization. While strong equivalence between two programs holds if they can be faithfully replaced by each other in any context (facts and rules), uniform equivalence amounts to equivalent behavior of programs under any set of facts. Both notions (as well as several variants thereof) have been extensively studied. However, the somewhat reverse notion of equivalence which holds if two programs are equivalent under the addition of any set of proper rules (i.e., all rules except facts) has not been investigated yet. In this paper, we close this gap and give a thorough study of this notion, which we call rule equivalence, and its parameterized version where we allow facts over a given restricted alphabet to appear in the context. This notion of equivalence is thus a relationship between two programs whose input is (partially) fixed but where additional proper rules might still be added. Such a notion might be helpful in debugging of programs. We give full characterization results and a complexity analysis for the propositional case of rule equivalence and its relativized versions. Moreover, we address the problem of program simplification under rule equivalence. Finally, we show that rule equivalence is decidable in the non-ground case. Keywords Answer set programming * Equivalence Mathematics Subject Classification (2010) 68N17 |
| Audience | Academic |
| Author | Woltran, Stefan Bliem, Bernhard |
| Author_xml | – sequence: 1 givenname: Bernhard surname: Bliem fullname: Bliem, Bernhard email: bliem@dbai.tuwien.ac.at organization: Institute of Information SystemsTU Wien – sequence: 2 givenname: Stefan orcidid: 0000-0003-1594-8972 surname: Woltran fullname: Woltran, Stefan organization: Institute of Information SystemsTU Wien |
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| Cites_doi | 10.1145/383779.383783 10.1145/1243996.1244000 10.1080/11663081.2013.799318 10.1023/A:1018978005636 10.1145/1149114.1149117 10.1145/2043174.2043195 10.1613/jair.2810 10.1017/S1471068410000542 10.1007/978-3-540-24609-1_18 10.1007/978-3-540-30227-8_17 10.1007/978-3-540-30227-8_16 10.1007/978-3-540-24609-1_10 10.1007/978-3-540-24599-5_16 10.1007/978-3-319-30024-5_6 10.1016/B978-0-934613-40-8.50021-X |
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| SubjectTerms | Artificial Intelligence Complex Systems Computer Science Context Declarative programming Equivalence Investigations Logic programs Mathematical programming Mathematics Modularity Problem solving |
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| Title | Equivalence between answer-set programs under (partially) fixed input |
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