TopLog
TopLog: ILP using a logic program declarative bias. This paper introduces a new Inductive Logic Programming (ILP) framework called Top Directed Hypothesis Derivation (TDHD). In this framework each hypothesised clause must be derivable from a given logic program called top theory (⊤). The top theory can be viewed as a declarative bias which defines the hypothesis space. This replaces the metalogical mode statements which are used in many ILP systems. Firstly, we present a theoretical framework for TDHD and show that standard SLD derivation can be used to efficiently derive hypotheses from ⊤. Secondly, we present a prototype implementation of TDHD within a new ILP system called TopLog. Thirdly, we show that the accuracy and efficiency of TopLog, on several benchmark datasets, is competitive with a state of the art ILP system like Aleph
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References in zbMATH (referenced in 10 articles , 1 standard article )
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Sorted by year (- Patsantzis, S.; Muggleton, S. H.: Top program construction and reduction for polynomial time meta-interpretive learning (2021)
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- Muggleton, Stephen H.; Lin, Dianhuan; Pahlavi, Niels; Tamaddoni-Nezhad, Alireza: Meta-interpretive learning: application to grammatical inference (2014)
- Inoue, Katsumi; Doncescu, Andrei; Nabeshima, Hidetomo: Completing causal networks by meta-level abduction (2013)
- Srinivasan, Ashwin; Faruquie, Tanveer A.; Joshi, Sachindra: Data and task parallelism in ILP using mapreduce (2012)
- Corapi, Domenico; Russo, Alessandra; Lupu, Emil: Inductive logic programming as abductive search (2010)
- Srinivasan, Ashwin; Ramakrishnan, Ganesh: Parameter screening and optimisation for ILP using designed experiments (2010) ioport
- Muggleton, Stephen H.; Santos, José Carlos Almeida; Tamaddoni-Nezhad, Alireza: TopLog: ILP using a logic program declarative bias (2008)
- Santos, José Carlos Almeida: TopLog: ILP using a logic program declarative bias (2008) ioport