Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations
Abstract Several different semantics have been proposed for conditional knowledge bases $\mathcal {R}$ containing qualitative conditionals of the form “If A, then usually B”, leading to different nonmonotonic inference relations induced by $\mathcal {R}$. For the notion of c-representations which ar...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Beierle, Christoph [verfasserIn] Kutsch, Steven [verfasserIn] Sauerwald, Kai [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Annals of mathematics and artificial intelligence - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990, 87(2019), 1-2 vom: 30. Aug., Seite 5-41 |
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| Übergeordnetes Werk: |
volume:87 ; year:2019 ; number:1-2 ; day:30 ; month:08 ; pages:5-41 |
| Links: |
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| DOI / URN: |
10.1007/s10472-019-09653-7 |
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| Katalog-ID: |
SPR010340130 |
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| 245 | 1 | 0 | |a Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations |
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| 520 | |a Abstract Several different semantics have been proposed for conditional knowledge bases $\mathcal {R}$ containing qualitative conditionals of the form “If A, then usually B”, leading to different nonmonotonic inference relations induced by $\mathcal {R}$. For the notion of c-representations which are a subclass of all ranking functions accepting $\mathcal {R}$, a skeptical inference relation, called c-inference and taking all c-representations of $\mathcal {R}$ into account, has been suggested. In this article, we develop a 3-phase compilation scheme for both knowledge bases and skeptical queries to constraint satisfaction problems. In addition to skeptical c-inference, we show how also credulous and weakly skeptical c-inference can be modelled as constraint satisfaction problems, and that the compilation scheme can be extended to such queries. We further extend the compilation approach to knowledge bases evolving over time. The compiled form of $\mathcal {R}$ is reused for incrementally compiling extensions, contractions, and updates of $\mathcal {R}$. For each compilation step, we prove its soundness and completeness, and demonstrate significant efficiency benefits when querying the compiled version of $\mathcal {R}$. These findings are also supported by experiments with the software system InfOCF that employs the proposed compilation scheme. | ||
| 650 | 4 | |a Conditional |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Conditional knowledge base |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a c-representation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Skeptical c-inference |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Weakly skeptical c-inference |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Credulous c-inference |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Constraint satisfaction problem |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Knowledge base compilation |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Knowledge base modification |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Incremental compilation |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Kutsch, Steven |e verfasserin |4 aut | |
| 700 | 1 | |a Sauerwald, Kai |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Annals of mathematics and artificial intelligence |d Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 |g 87(2019), 1-2 vom: 30. Aug., Seite 5-41 |w (DE-627)320424154 |w (DE-600)2002961-5 |x 1573-7470 |7 nnns |
| 773 | 1 | 8 | |g volume:87 |g year:2019 |g number:1-2 |g day:30 |g month:08 |g pages:5-41 |
| 856 | 4 | 0 | |u https://dx.doi.org/10.1007/s10472-019-09653-7 |z lizenzpflichtig |3 Volltext |
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10.1007/s10472-019-09653-7 doi (DE-627)SPR010340130 (SPR)s10472-019-09653-7-e DE-627 ger DE-627 rakwb eng 510 004 ASE 54.72 bkl 31.00 bkl Beierle, Christoph verfasserin aut Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Several different semantics have been proposed for conditional knowledge bases $\mathcal {R}$ containing qualitative conditionals of the form “If A, then usually B”, leading to different nonmonotonic inference relations induced by $\mathcal {R}$. For the notion of c-representations which are a subclass of all ranking functions accepting $\mathcal {R}$, a skeptical inference relation, called c-inference and taking all c-representations of $\mathcal {R}$ into account, has been suggested. In this article, we develop a 3-phase compilation scheme for both knowledge bases and skeptical queries to constraint satisfaction problems. In addition to skeptical c-inference, we show how also credulous and weakly skeptical c-inference can be modelled as constraint satisfaction problems, and that the compilation scheme can be extended to such queries. We further extend the compilation approach to knowledge bases evolving over time. The compiled form of $\mathcal {R}$ is reused for incrementally compiling extensions, contractions, and updates of $\mathcal {R}$. For each compilation step, we prove its soundness and completeness, and demonstrate significant efficiency benefits when querying the compiled version of $\mathcal {R}$. These findings are also supported by experiments with the software system InfOCF that employs the proposed compilation scheme. Conditional (dpeaa)DE-He213 Conditional knowledge base (dpeaa)DE-He213 c-representation (dpeaa)DE-He213 Skeptical c-inference (dpeaa)DE-He213 Weakly skeptical c-inference (dpeaa)DE-He213 Credulous c-inference (dpeaa)DE-He213 Constraint satisfaction problem (dpeaa)DE-He213 Knowledge base compilation (dpeaa)DE-He213 Knowledge base modification (dpeaa)DE-He213 Incremental compilation (dpeaa)DE-He213 Kutsch, Steven verfasserin aut Sauerwald, Kai verfasserin aut Enthalten in Annals of mathematics and artificial intelligence Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 87(2019), 1-2 vom: 30. Aug., Seite 5-41 (DE-627)320424154 (DE-600)2002961-5 1573-7470 nnns volume:87 year:2019 number:1-2 day:30 month:08 pages:5-41 https://dx.doi.org/10.1007/s10472-019-09653-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.72 ASE 31.00 ASE AR 87 2019 1-2 30 08 5-41 |
| spelling |
10.1007/s10472-019-09653-7 doi (DE-627)SPR010340130 (SPR)s10472-019-09653-7-e DE-627 ger DE-627 rakwb eng 510 004 ASE 54.72 bkl 31.00 bkl Beierle, Christoph verfasserin aut Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Several different semantics have been proposed for conditional knowledge bases $\mathcal {R}$ containing qualitative conditionals of the form “If A, then usually B”, leading to different nonmonotonic inference relations induced by $\mathcal {R}$. For the notion of c-representations which are a subclass of all ranking functions accepting $\mathcal {R}$, a skeptical inference relation, called c-inference and taking all c-representations of $\mathcal {R}$ into account, has been suggested. In this article, we develop a 3-phase compilation scheme for both knowledge bases and skeptical queries to constraint satisfaction problems. In addition to skeptical c-inference, we show how also credulous and weakly skeptical c-inference can be modelled as constraint satisfaction problems, and that the compilation scheme can be extended to such queries. We further extend the compilation approach to knowledge bases evolving over time. The compiled form of $\mathcal {R}$ is reused for incrementally compiling extensions, contractions, and updates of $\mathcal {R}$. For each compilation step, we prove its soundness and completeness, and demonstrate significant efficiency benefits when querying the compiled version of $\mathcal {R}$. These findings are also supported by experiments with the software system InfOCF that employs the proposed compilation scheme. Conditional (dpeaa)DE-He213 Conditional knowledge base (dpeaa)DE-He213 c-representation (dpeaa)DE-He213 Skeptical c-inference (dpeaa)DE-He213 Weakly skeptical c-inference (dpeaa)DE-He213 Credulous c-inference (dpeaa)DE-He213 Constraint satisfaction problem (dpeaa)DE-He213 Knowledge base compilation (dpeaa)DE-He213 Knowledge base modification (dpeaa)DE-He213 Incremental compilation (dpeaa)DE-He213 Kutsch, Steven verfasserin aut Sauerwald, Kai verfasserin aut Enthalten in Annals of mathematics and artificial intelligence Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 87(2019), 1-2 vom: 30. Aug., Seite 5-41 (DE-627)320424154 (DE-600)2002961-5 1573-7470 nnns volume:87 year:2019 number:1-2 day:30 month:08 pages:5-41 https://dx.doi.org/10.1007/s10472-019-09653-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.72 ASE 31.00 ASE AR 87 2019 1-2 30 08 5-41 |
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10.1007/s10472-019-09653-7 doi (DE-627)SPR010340130 (SPR)s10472-019-09653-7-e DE-627 ger DE-627 rakwb eng 510 004 ASE 54.72 bkl 31.00 bkl Beierle, Christoph verfasserin aut Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Several different semantics have been proposed for conditional knowledge bases $\mathcal {R}$ containing qualitative conditionals of the form “If A, then usually B”, leading to different nonmonotonic inference relations induced by $\mathcal {R}$. For the notion of c-representations which are a subclass of all ranking functions accepting $\mathcal {R}$, a skeptical inference relation, called c-inference and taking all c-representations of $\mathcal {R}$ into account, has been suggested. In this article, we develop a 3-phase compilation scheme for both knowledge bases and skeptical queries to constraint satisfaction problems. In addition to skeptical c-inference, we show how also credulous and weakly skeptical c-inference can be modelled as constraint satisfaction problems, and that the compilation scheme can be extended to such queries. We further extend the compilation approach to knowledge bases evolving over time. The compiled form of $\mathcal {R}$ is reused for incrementally compiling extensions, contractions, and updates of $\mathcal {R}$. For each compilation step, we prove its soundness and completeness, and demonstrate significant efficiency benefits when querying the compiled version of $\mathcal {R}$. These findings are also supported by experiments with the software system InfOCF that employs the proposed compilation scheme. Conditional (dpeaa)DE-He213 Conditional knowledge base (dpeaa)DE-He213 c-representation (dpeaa)DE-He213 Skeptical c-inference (dpeaa)DE-He213 Weakly skeptical c-inference (dpeaa)DE-He213 Credulous c-inference (dpeaa)DE-He213 Constraint satisfaction problem (dpeaa)DE-He213 Knowledge base compilation (dpeaa)DE-He213 Knowledge base modification (dpeaa)DE-He213 Incremental compilation (dpeaa)DE-He213 Kutsch, Steven verfasserin aut Sauerwald, Kai verfasserin aut Enthalten in Annals of mathematics and artificial intelligence Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 87(2019), 1-2 vom: 30. Aug., Seite 5-41 (DE-627)320424154 (DE-600)2002961-5 1573-7470 nnns volume:87 year:2019 number:1-2 day:30 month:08 pages:5-41 https://dx.doi.org/10.1007/s10472-019-09653-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.72 ASE 31.00 ASE AR 87 2019 1-2 30 08 5-41 |
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10.1007/s10472-019-09653-7 doi (DE-627)SPR010340130 (SPR)s10472-019-09653-7-e DE-627 ger DE-627 rakwb eng 510 004 ASE 54.72 bkl 31.00 bkl Beierle, Christoph verfasserin aut Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Several different semantics have been proposed for conditional knowledge bases $\mathcal {R}$ containing qualitative conditionals of the form “If A, then usually B”, leading to different nonmonotonic inference relations induced by $\mathcal {R}$. For the notion of c-representations which are a subclass of all ranking functions accepting $\mathcal {R}$, a skeptical inference relation, called c-inference and taking all c-representations of $\mathcal {R}$ into account, has been suggested. In this article, we develop a 3-phase compilation scheme for both knowledge bases and skeptical queries to constraint satisfaction problems. In addition to skeptical c-inference, we show how also credulous and weakly skeptical c-inference can be modelled as constraint satisfaction problems, and that the compilation scheme can be extended to such queries. We further extend the compilation approach to knowledge bases evolving over time. The compiled form of $\mathcal {R}$ is reused for incrementally compiling extensions, contractions, and updates of $\mathcal {R}$. For each compilation step, we prove its soundness and completeness, and demonstrate significant efficiency benefits when querying the compiled version of $\mathcal {R}$. These findings are also supported by experiments with the software system InfOCF that employs the proposed compilation scheme. Conditional (dpeaa)DE-He213 Conditional knowledge base (dpeaa)DE-He213 c-representation (dpeaa)DE-He213 Skeptical c-inference (dpeaa)DE-He213 Weakly skeptical c-inference (dpeaa)DE-He213 Credulous c-inference (dpeaa)DE-He213 Constraint satisfaction problem (dpeaa)DE-He213 Knowledge base compilation (dpeaa)DE-He213 Knowledge base modification (dpeaa)DE-He213 Incremental compilation (dpeaa)DE-He213 Kutsch, Steven verfasserin aut Sauerwald, Kai verfasserin aut Enthalten in Annals of mathematics and artificial intelligence Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 87(2019), 1-2 vom: 30. Aug., Seite 5-41 (DE-627)320424154 (DE-600)2002961-5 1573-7470 nnns volume:87 year:2019 number:1-2 day:30 month:08 pages:5-41 https://dx.doi.org/10.1007/s10472-019-09653-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.72 ASE 31.00 ASE AR 87 2019 1-2 30 08 5-41 |
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10.1007/s10472-019-09653-7 doi (DE-627)SPR010340130 (SPR)s10472-019-09653-7-e DE-627 ger DE-627 rakwb eng 510 004 ASE 54.72 bkl 31.00 bkl Beierle, Christoph verfasserin aut Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Several different semantics have been proposed for conditional knowledge bases $\mathcal {R}$ containing qualitative conditionals of the form “If A, then usually B”, leading to different nonmonotonic inference relations induced by $\mathcal {R}$. For the notion of c-representations which are a subclass of all ranking functions accepting $\mathcal {R}$, a skeptical inference relation, called c-inference and taking all c-representations of $\mathcal {R}$ into account, has been suggested. In this article, we develop a 3-phase compilation scheme for both knowledge bases and skeptical queries to constraint satisfaction problems. In addition to skeptical c-inference, we show how also credulous and weakly skeptical c-inference can be modelled as constraint satisfaction problems, and that the compilation scheme can be extended to such queries. We further extend the compilation approach to knowledge bases evolving over time. The compiled form of $\mathcal {R}$ is reused for incrementally compiling extensions, contractions, and updates of $\mathcal {R}$. For each compilation step, we prove its soundness and completeness, and demonstrate significant efficiency benefits when querying the compiled version of $\mathcal {R}$. These findings are also supported by experiments with the software system InfOCF that employs the proposed compilation scheme. Conditional (dpeaa)DE-He213 Conditional knowledge base (dpeaa)DE-He213 c-representation (dpeaa)DE-He213 Skeptical c-inference (dpeaa)DE-He213 Weakly skeptical c-inference (dpeaa)DE-He213 Credulous c-inference (dpeaa)DE-He213 Constraint satisfaction problem (dpeaa)DE-He213 Knowledge base compilation (dpeaa)DE-He213 Knowledge base modification (dpeaa)DE-He213 Incremental compilation (dpeaa)DE-He213 Kutsch, Steven verfasserin aut Sauerwald, Kai verfasserin aut Enthalten in Annals of mathematics and artificial intelligence Dordrecht [u.a.] : Springer Science + Business Media B.V, 1990 87(2019), 1-2 vom: 30. Aug., Seite 5-41 (DE-627)320424154 (DE-600)2002961-5 1573-7470 nnns volume:87 year:2019 number:1-2 day:30 month:08 pages:5-41 https://dx.doi.org/10.1007/s10472-019-09653-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OPC-MAT SSG-OPC-ASE GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.72 ASE 31.00 ASE AR 87 2019 1-2 30 08 5-41 |
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Conditional Conditional knowledge base c-representation Skeptical c-inference Weakly skeptical c-inference Credulous c-inference Constraint satisfaction problem Knowledge base compilation Knowledge base modification Incremental compilation |
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Beierle, Christoph @@aut@@ Kutsch, Steven @@aut@@ Sauerwald, Kai @@aut@@ |
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For the notion of c-representations which are a subclass of all ranking functions accepting $\mathcal {R}$, a skeptical inference relation, called c-inference and taking all c-representations of $\mathcal {R}$ into account, has been suggested. In this article, we develop a 3-phase compilation scheme for both knowledge bases and skeptical queries to constraint satisfaction problems. In addition to skeptical c-inference, we show how also credulous and weakly skeptical c-inference can be modelled as constraint satisfaction problems, and that the compilation scheme can be extended to such queries. We further extend the compilation approach to knowledge bases evolving over time. The compiled form of $\mathcal {R}$ is reused for incrementally compiling extensions, contractions, and updates of $\mathcal {R}$. For each compilation step, we prove its soundness and completeness, and demonstrate significant efficiency benefits when querying the compiled version of $\mathcal {R}$. 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Beierle, Christoph |
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Beierle, Christoph ddc 510 bkl 54.72 bkl 31.00 misc Conditional misc Conditional knowledge base misc c-representation misc Skeptical c-inference misc Weakly skeptical c-inference misc Credulous c-inference misc Constraint satisfaction problem misc Knowledge base compilation misc Knowledge base modification misc Incremental compilation Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations |
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510 004 ASE 54.72 bkl 31.00 bkl Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations Conditional (dpeaa)DE-He213 Conditional knowledge base (dpeaa)DE-He213 c-representation (dpeaa)DE-He213 Skeptical c-inference (dpeaa)DE-He213 Weakly skeptical c-inference (dpeaa)DE-He213 Credulous c-inference (dpeaa)DE-He213 Constraint satisfaction problem (dpeaa)DE-He213 Knowledge base compilation (dpeaa)DE-He213 Knowledge base modification (dpeaa)DE-He213 Incremental compilation (dpeaa)DE-He213 |
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ddc 510 bkl 54.72 bkl 31.00 misc Conditional misc Conditional knowledge base misc c-representation misc Skeptical c-inference misc Weakly skeptical c-inference misc Credulous c-inference misc Constraint satisfaction problem misc Knowledge base compilation misc Knowledge base modification misc Incremental compilation |
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Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations |
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Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations |
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compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations |
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Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations |
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Abstract Several different semantics have been proposed for conditional knowledge bases $\mathcal {R}$ containing qualitative conditionals of the form “If A, then usually B”, leading to different nonmonotonic inference relations induced by $\mathcal {R}$. For the notion of c-representations which are a subclass of all ranking functions accepting $\mathcal {R}$, a skeptical inference relation, called c-inference and taking all c-representations of $\mathcal {R}$ into account, has been suggested. In this article, we develop a 3-phase compilation scheme for both knowledge bases and skeptical queries to constraint satisfaction problems. In addition to skeptical c-inference, we show how also credulous and weakly skeptical c-inference can be modelled as constraint satisfaction problems, and that the compilation scheme can be extended to such queries. We further extend the compilation approach to knowledge bases evolving over time. The compiled form of $\mathcal {R}$ is reused for incrementally compiling extensions, contractions, and updates of $\mathcal {R}$. For each compilation step, we prove its soundness and completeness, and demonstrate significant efficiency benefits when querying the compiled version of $\mathcal {R}$. These findings are also supported by experiments with the software system InfOCF that employs the proposed compilation scheme. |
| abstractGer |
Abstract Several different semantics have been proposed for conditional knowledge bases $\mathcal {R}$ containing qualitative conditionals of the form “If A, then usually B”, leading to different nonmonotonic inference relations induced by $\mathcal {R}$. For the notion of c-representations which are a subclass of all ranking functions accepting $\mathcal {R}$, a skeptical inference relation, called c-inference and taking all c-representations of $\mathcal {R}$ into account, has been suggested. In this article, we develop a 3-phase compilation scheme for both knowledge bases and skeptical queries to constraint satisfaction problems. In addition to skeptical c-inference, we show how also credulous and weakly skeptical c-inference can be modelled as constraint satisfaction problems, and that the compilation scheme can be extended to such queries. We further extend the compilation approach to knowledge bases evolving over time. The compiled form of $\mathcal {R}$ is reused for incrementally compiling extensions, contractions, and updates of $\mathcal {R}$. For each compilation step, we prove its soundness and completeness, and demonstrate significant efficiency benefits when querying the compiled version of $\mathcal {R}$. These findings are also supported by experiments with the software system InfOCF that employs the proposed compilation scheme. |
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Abstract Several different semantics have been proposed for conditional knowledge bases $\mathcal {R}$ containing qualitative conditionals of the form “If A, then usually B”, leading to different nonmonotonic inference relations induced by $\mathcal {R}$. For the notion of c-representations which are a subclass of all ranking functions accepting $\mathcal {R}$, a skeptical inference relation, called c-inference and taking all c-representations of $\mathcal {R}$ into account, has been suggested. In this article, we develop a 3-phase compilation scheme for both knowledge bases and skeptical queries to constraint satisfaction problems. In addition to skeptical c-inference, we show how also credulous and weakly skeptical c-inference can be modelled as constraint satisfaction problems, and that the compilation scheme can be extended to such queries. We further extend the compilation approach to knowledge bases evolving over time. The compiled form of $\mathcal {R}$ is reused for incrementally compiling extensions, contractions, and updates of $\mathcal {R}$. For each compilation step, we prove its soundness and completeness, and demonstrate significant efficiency benefits when querying the compiled version of $\mathcal {R}$. These findings are also supported by experiments with the software system InfOCF that employs the proposed compilation scheme. |
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Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations |
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| score |
7.399069 |