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- W4293763670 abstract "Significant research has been conducted in recent years to extend Inductive Logic Programming (ILP) methods to induce Answer Set Programs (ASP). These methods perform an exhaustive search for the correct hypothesis by encoding an ILP problem instance as an ASP program. Exhaustive search, however, results in loss of scalability. In addition, the language bias employed in these methods is overly restrictive too. In this paper we extend our previous work on learning stratified answer set programs that have a single stable model to learning arbitrary (i.e., non-stratified) ones with multiple stable models. Our extended algorithm is a greedy FOIL-like algorithm, capable of inducing non-monotonic logic programs, examples of which includes programs for combinatorial problems such as graph-coloring and N-queens. To the best of our knowledge, this is the first heuristic-based ILP algorithm to induce answer set programs with multiple stable models." @default.
- W4293763670 created "2022-08-31" @default.
- W4293763670 creator A5003055908 @default.
- W4293763670 creator A5067377863 @default.
- W4293763670 date "2018-02-18" @default.
- W4293763670 modified "2023-09-25" @default.
- W4293763670 title "Heuristic Based Induction of Answer Set Programs: From Default theories to combinatorial problems" @default.
- W4293763670 doi "https://doi.org/10.48550/arxiv.1802.06462" @default.
- W4293763670 hasPublicationYear "2018" @default.
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