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In this paper we extend RPBL, a Relational Paths Based Learning approach for first order theories in three directions. We apply domain theories to expand structured instance space, learn recursive theories by an example of learningmember relationship of lists, and analyze the performance as well as time complexity theoretically. In addition, we give the details of our experimental results.
In this paper, we propose a simultaneous covering inductive logic programming approach RPBL (relational paths-based learning). It uses relational paths as explanations for positive training examples to overcome the explosion problem existed in standard inductive logic programming. It benefits greatly from a simultaneous covering strategy, and avoids local maxima and local plateaus. Experimental results...
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