Evolutionary Algorithm Software Factory (EA-SoFa)
Department
Computer Science
Major
Computer Science
Research Advisor
Tauritz, Daniel R.
Advisor's Department
Computer Science
Funding Source
Missouri S&T Opportunities for Undergraduate Research Experiences (OURE) Program
Abstract
Evolutionary Algorithms (EAs) have shown great promise in solving complex real-world problems. However, there is a great lack of a standardized, thoroughly documented, and continuously maintained open-source research community resource containing industry-quality implementations of the field's classic and state-of-the-art algorithms. This project takes the first steps in providing this resource by creating an Internet-based software factory for EAs which takes as input an algorithm specification and provides as output the associated source code in the specified programming language. This resource will also include the pseudocode for the implemented EAs as well as links to the seminal papers in which the algorithms were published. This project will benefit researchers, educators, and practitioners that use EAs by providing a single resource to obtain standardized EA implementations.
Biography
George Rush is an undergraduate in the Computer Science Department. His research focuses primarily on evolutionary computation, and his interests include autonomic computing, artificial intelligence, and data mining. He will be graduating with his BS in Computer Science and a minor in Applied Mathematics in May 2010. Afterwards he plans to work for AT&T as an Associate IT Analyst and eventually pursue a Master’s degree in Artificial Intelligence.
Research Category
Sciences
Presentation Type
Oral Presentation
Document Type
Presentation
Location
Turner Room
Presentation Date
07 Apr 2010, 9:30 am - 10:00 am
Evolutionary Algorithm Software Factory (EA-SoFa)
Turner Room
Evolutionary Algorithms (EAs) have shown great promise in solving complex real-world problems. However, there is a great lack of a standardized, thoroughly documented, and continuously maintained open-source research community resource containing industry-quality implementations of the field's classic and state-of-the-art algorithms. This project takes the first steps in providing this resource by creating an Internet-based software factory for EAs which takes as input an algorithm specification and provides as output the associated source code in the specified programming language. This resource will also include the pseudocode for the implemented EAs as well as links to the seminal papers in which the algorithms were published. This project will benefit researchers, educators, and practitioners that use EAs by providing a single resource to obtain standardized EA implementations.
