Title

Evolutionary Algorithm Software Factory (EA-SoFa)

Presenter Information

George Rush

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

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Apr 7th, 9:30 AM Apr 7th, 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.