Abstract
Evolutionary algorithms are used a lot to solve non-polynomial problems. This works especially well since it has already been shown that they are able to find near-optimal solutions. This project will look focus on the genetic algorithm (GA) and the population based incremental learning algorithm (PBIL). This paper will then take the PBIL and add functionality to the PBIL to create the population based incremental schema learning (PBISL) algorithm which uses the notion of schemata from the GA. The objective of this paper is to create a PBISL and compare it against a PBIL and a genetic algorithm. This comparison will be done by comparing the results of different problems like the parity, 0/1 knapsack and the traveling salesman problem.
Advisor
Brown, Dale A.
Department
Computer Science
Recommended Citation
Dominski, Matthew S., "Population Based Incremental Schema Learning" (2008). Senior Independent Study Theses. Paper 699.
https://openworks.wooster.edu/independentstudy/699
Publication Date
2008
Degree Granted
Bachelor of Arts
Document Type
Senior Independent Study Thesis
© Copyright 2008 Matthew S. Dominski