Genetics-Based Learning and Statistical Generalization
Benjamin Wan-Sang Wah, Arthur Ieumwananonthachai, Ting Jung Yu · Knowledge-Based Systems · 1997
Introduction Heuristics are generally used in many real-world engineering applications ranging from computer aided design, optimization, scheduling and computer communications. Since the relationship between performance and control is unknown in heuristics, some parameters, functions, and procedures are designed either based on user experience or experimentally. These heuristics can usually be improved by automated tuning, machine learning, and generalization. In this chapter, we study the problem of performance generalization of the heuristics learned. 1.1 Terminologies We define a problem solver as an algorithm, or more generally, a software package used to solve a problem. A problem solver can be regarded as a black box, with some heuristic components or heuristics designed in an ad hoc way, where a heuristic is "A process that may solve a problem but offers no guarantees of doing so" 1 . Heu