Sofia Benbelkacem, Baghdad Atmani, Mohamed Benamina, University of Oran, Algeria

In Artificial Intelligence, planning refers to an area of research that proposes to develop systems that can automatically generate a result set, in the form of an integrated decision-making system through a formal procedure, known as plan. Instead of resorting to the scheduling algorithms to generate plans, it is proposed to operate the automatic learning by decision tree to optimize time. In this paper, we propose to build a classification model by induction graph from a learning sample containing plans that have an associated set of descriptors whose values change depending on each plan. This model will then operate for classifying new cases by assigning the appropriate plan.

Bloksworld, Classification, Data Mining, Decision Tree, Planning, Induction Graph, Symbolic Induction