Learning heuristic functions for numeric optimization problems

Provides a framework for approaching the learning of heuristic functions for numeric optimization problem solutions. The outline of a system called ´Techniques using Experimentation for Acquisition and Creation of HeuRistics 2.0´ (TEACHER 2.0), for learning heuristic functions is presented. The system is unique in that it combines many learning techniques into one coherent system. It can be a powerful learning system as it allows the generation of heuristics based on an amalgamation of learning techniques and strategies. The value of the system is illustrated by an example in which TEACHER 2.0 learns a new heuristic that is superior to the typical heuristic for that problem domain.<>