Explanation-based learning

Intelligence in Numerical Computing improving Batch Scheduling Algorithms through Explanation-Based Learning... 

First-order horn clause logic is the representation that has been adopted by workers in the field of explanation-based learning (Minton et al., 1990). Hence, using this representation allows us take advantage of the results and algorithms developed in that field to carry out the machine learning task. 

In this section, we will briefly outline the method of explanation-based learning that we use to carry out the synthesis of new control conditions. This method has become well established within the AI community, and for more details, see Minton et al. (1990), Dejong (1990), and Mitchell et al. (1986). 

The following definition of explanation-based learning is taken from Minton et al. (1990). 

So far we have described all the inputs to the explanation-based learning procedure. We must now describe a few of the basic feature of the algorithm itself. 

Dejong, G., and Mooney, R., Explanation-based learning An alternate view. Mach. Learn. 1, 145-176 (1986). 

Mooney, R.J., A General Explanation-Based Learning Mechanism and its Application to Narrative Understanding. Morgan Kaufmann, San Mateo, CA (1990). 

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