Parallel Execution for Speeding Up Inductive Logic Programming Systems
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This paper describes a parallel algorithm and its implementation for a hypothesis space search in Inductive Logic Programming (ILP). A typical ILP system, Progol, regards induction as a search problem for finding a hypothesis, and an efficient search algorithm is used to find the optimal hypothesis. In this paper, we formalize the ILP task as a generalized branch-and-bound search and propose three methods of parallel executions for the optimal search. These methods are implemented in KL1, a parallel logic programming language, and are analyzed for execution speed and load balancing. An experiment on a benchmark test set was conducted using a shared memory parallel machine to evaluate the performance of the hypothesis search according to the number of processors. The result demonstrates that the statistics obtained coincide with the expected degree of parallelism.
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- Parallel Execution for Speeding Up Inductive Logic Programming Systems
- Book Title
- Discovery Science
- Book Subtitle
- Second International Conference, DS’99 Tokyo, Japan, December 6–8, 1999 Proceedings
- pp 277-286
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- Lecture Notes in Computer Science
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- Springer Berlin Heidelberg
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- Springer-Verlag Berlin Heidelberg
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- Editor Affiliations
- 1. Department of Informatics, Kyushu University
- 2. Graduate School of Media and Governance, Keio University
- Author Affiliations
- 5. Faculty of Sci. and Tech., Science University of Tokyo Noda, Chiba, 278-8510, Japan
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