Heuristic Based Induction of Answer Set Programs: From Default theories to combinatorial problems
نویسندگان
چکیده
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 graphcoloring 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.
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عنوان ژورنال:
- CoRR
دوره abs/1802.06462 شماره
صفحات -
تاریخ انتشار 2018