Alternative Bloat Control Methods
نویسندگان
چکیده
Bloat control is an important aspect of evolutionary computation methods, such as genetic programming, which must deal with genomes of arbitrary size. We introduce three new methods for bloat control: Biased Multi-Objective Parsimony Pressure (BMOPP), the Waiting Room, and Death by Size. These methods are unusual approaches to bloat control, and are not only useful in various circumstances, but two of them suggest novel approaches to attack the problem. BMOPP is a more traditional parsimony-pressure style bloat control method, while the other two methods do not consider parsimony as part of the selection process at all, but instead penalize for parsimony at other stages in the evolutionary process. We find parameter settings for BMOPP and the Waiting Room which are effective across all tested problem domains. Death by Size does not appear to have this consistency, but we find it a useful tool as it has particular applicability to steady-state evolution.
منابع مشابه
A Comparison of Bloat Control Methods for Genetic Programming
Genetic programming has highlighted the problem of bloat, the uncontrolled growth of the average size of an individual in the population. The most common approach to dealing with bloat in tree-based genetic programming individuals is to limit their maximal allowed depth. An alternative to depth limiting is to punish individuals in some way based on excess size, and our experiments have shown th...
متن کاملImproving Generalization Ability of Genetic Programming: Comparative Study
In the field of empirical modeling using Genetic Programming (GP), it is important to evolve solution with good generalization ability. Generalization ability of GP solutions get affected by two important issues: bloat and over-fitting. Bloat is uncontrolled growth of code without any gain in fitness and important issue in GP. We surveyed and classified existing literature related to different ...
متن کاملCode Bloat Problem in Genetic Programming
The concept of “bloat” in Genetic Programming is a well-established phenomenon characterized by variable-length genomes gradually increasing in size during evolution [1]. Bloat hampers the efficiency and ability of genetic programming for solving problems. A range of explanations have been proposed for the problem of bloat, including destructive crossover and mutation operators, selection press...
متن کاملGenetic program based data mining of fuzzy decision trees and methods of improving convergence and reducing bloat
A data mining procedure for automatic determination of fuzzy decision tree structure using a genetic program (GP) is discussed. A GP is an algorithm that evolves other algorithms or mathematical expressions. Innovative methods for accelerating convergence of the data mining procedure and reducing bloat are given. In genetic programming, bloat refers to excessive tree growth. It has been observe...
متن کاملPreliminary Study of Bloat in Genetic Programming with Behavior-Based Search
Bloat is one of the most interesting theoretical problems in genetic programming (GP), and one of the most important pragmatic limitations in the development of real-world GP solutions. Over the years, many theories regarding the causes of bloat have been proposed and a variety of bloat control methods have been developed. It seems that one of the underlying causes of bloat is the search for fi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2004