Communications of the ACM
Machine learning an artificial intelligence approach volume II
Machine learning an artificial intelligence approach volume II
C4.5: programs for machine learning
C4.5: programs for machine learning
Learning procedural knowledge through observation
Proceedings of the 1st international conference on Knowledge capture
A Framework for Behavioural Cloning
Machine Intelligence 15, Intelligent Agents [St. Catherine's College, Oxford, July 1995]
A Model of Children's Vocabulary Acquisition Using Inductive Logic Programming
DS '99 Proceedings of the Second International Conference on Discovery Science
Inductive Synthesis of Functional Programs: Universal Planning, Folding of Finite Programs, and Schema Abstraction by Analogical Reasoning
Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach
The Journal of Machine Learning Research
Learning Recursive Control Programs from Problem Solving
The Journal of Machine Learning Research
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In mathematics, a sequence of sentences describes how to solve a problem; for instance, sentences, "Calculate the least common multiple of 10 and 15. Firstly divide 10 and 15 by 2. Results are '5' and 'cannot divide'. '5' and 'cannot divide' are not 1 and 1. Divide 5 and 15 by 2. Results are 'cannot divide' and 'cannot divide'." and so on, describe how to calculate the least common multiple of 10 and 15. While example sequences of sentences are given to our program, the program transforms the example sequences to generate a procedure, pG, to solve a problem. For instance, a generated procedure, pGp, checks if a given number is a prime number, another procedure, pGc, calculates the least common multiple of any two numbers, and another procedure, pGf, adds given two fractions. This paper explains our program that generates procedures, one after another, each of which solves one mathematical problem. The paper also argues, as a result of generating a procedure, pG, the meaning of a sentence (or sentences) is represented in the generated procedure, pG.