ProLogICA: a practical system for Abductive Logic Programming

Oliver Ray; Antonis Kakas; J. Dix; A Hunter

ProLogICA: a practical system for Abductive Logic Programming

Oliver Ray, Antonis Kakas, J. Dix, A Hunter

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Abstract

This paper presents a new system called ProLogICA for Abductive Logic Programming (ALP) with Negation as Failure (NAF) and Integrity Constraints (ICs). The system builds upon existing ALP techniques but includes several optimisations and extensions necessitated by recent applications in computational biology, temporal reasoning and machine learning. Unlike some other ALP systems that support non-ground abduction through the integrated use of constraint solving, we adopt a more lightweight approach which avoids this complexity at the expense of only computing ground hypotheses. We argue our approach is suited to a wide class of real-world problems and demonstrate the effectiveness of \ProLogICA\ on three non-trivial applications.

Translated title of the contribution	ProLogICA: a practical system for Abductive Logic Programming
Original language	English
Title of host publication	11th International Workshop on Non-monotonic Reasoning
Publication status	Published - 2006

Bibliographical note

Other page information: 304-312
Conference Proceedings/Title of Journal: 11th International Workshop on Non-monotonic Reasoning
Other identifier: 2000635

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@inproceedings{db87dd6bc3fe4a808bc432eea52c3b9f,

title = "ProLogICA: a practical system for Abductive Logic Programming",

abstract = "This paper presents a new system called ProLogICA for Abductive Logic Programming (ALP) with Negation as Failure (NAF) and Integrity Constraints (ICs). The system builds upon existing ALP techniques but includes several optimisations and extensions necessitated by recent applications in computational biology, temporal reasoning and machine learning. Unlike some other ALP systems that support non-ground abduction through the integrated use of constraint solving, we adopt a more lightweight approach which avoids this complexity at the expense of only computing ground hypotheses. We argue our approach is suited to a wide class of real-world problems and demonstrate the effectiveness of \textbackslash{}ProLogICA\textbackslash{} on three non-trivial applications. ",

author = "Oliver Ray and Antonis Kakas and J. Dix and A Hunter",

note = "Other page information: 304-312 Conference Proceedings/Title of Journal: 11th International Workshop on Non-monotonic Reasoning Other identifier: 2000635",

year = "2006",

language = "English",

booktitle = "11th International Workshop on Non-monotonic Reasoning",

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T1 - ProLogICA: a practical system for Abductive Logic Programming

AU - Ray, Oliver

AU - Kakas, Antonis

AU - Dix, J.

AU - Hunter, A

N1 - Other page information: 304-312 Conference Proceedings/Title of Journal: 11th International Workshop on Non-monotonic Reasoning Other identifier: 2000635

PY - 2006

Y1 - 2006

N2 - This paper presents a new system called ProLogICA for Abductive Logic Programming (ALP) with Negation as Failure (NAF) and Integrity Constraints (ICs). The system builds upon existing ALP techniques but includes several optimisations and extensions necessitated by recent applications in computational biology, temporal reasoning and machine learning. Unlike some other ALP systems that support non-ground abduction through the integrated use of constraint solving, we adopt a more lightweight approach which avoids this complexity at the expense of only computing ground hypotheses. We argue our approach is suited to a wide class of real-world problems and demonstrate the effectiveness of \ProLogICA\ on three non-trivial applications.

AB - This paper presents a new system called ProLogICA for Abductive Logic Programming (ALP) with Negation as Failure (NAF) and Integrity Constraints (ICs). The system builds upon existing ALP techniques but includes several optimisations and extensions necessitated by recent applications in computational biology, temporal reasoning and machine learning. Unlike some other ALP systems that support non-ground abduction through the integrated use of constraint solving, we adopt a more lightweight approach which avoids this complexity at the expense of only computing ground hypotheses. We argue our approach is suited to a wide class of real-world problems and demonstrate the effectiveness of \ProLogICA\ on three non-trivial applications.

M3 - Conference Contribution (Conference Proceeding)

BT - 11th International Workshop on Non-monotonic Reasoning

ER -

ProLogICA: a practical system for Abductive Logic Programming

Abstract

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