An LCS Review for Beginners and Non-Computer Scientists.

I am pleased to share with you that the Journal of Artificial Evolution and Applications has recently published my LCS Review paper entitled, “Learning Classifier Systems: A Complete Introduction, Review, and Roadmap”. I wrote this from the perspective of a non-computer scientist, to introduce the basic LCS concept, as well as the variation represented in different LCS implementations that have been tasked to different problem domains. It was my goal and hope that this review might provide a reasonable starting point for outsiders interested in understanding or getting involved in the LCS community. This paper may be viewed using the following link: Thanks! I enjoyed listening to the many excellent GBML talks given at GECCO this year.

http://www.hindawi.com/journals/jaea/aip.736398.pdf

Data-Intensive Computing for Competent Genetic Algorithms: A Pilot Study using Meandre

Below you may find the slides I used during GECCO 2009 to present the paper titled “Data-Intensive Computing for Competent Genetic Algorithms: A Pilot Study using Meandre”. An early preprint in form of technical report can be found as an IlliGAL TR No. 2009001 or the full paper at the ACM digital library

Related […]

Related posts:

  1. Data-Intensive Computing for Competent Genetic Algorithms: A Pilot Study using Meandre
  2. Meandre: Semantic-Driven Data-Intensive Flows in the Clouds
  3. Scaling Genetic Algorithms using MapReduce

Below you may find the slides I used during GECCO 2009 to present the paper titled “Data-Intensive Computing for Competent Genetic Algorithms: A Pilot Study using Meandre”. An early preprint in form of technical report can be found as an IlliGAL TR No. 2009001 or the full paper at the ACM digital library

Related posts:

  1. Data-Intensive Computing for Competent Genetic Algorithms: A Pilot Study using Meandre
  2. Meandre: Semantic-Driven Data-Intensive Flows in the Clouds
  3. Scaling Genetic Algorithms using MapReduce

Data-Intensive Computing for Competent Genetic Algorithms: A Pilot Study using Meandre

by Llorà, X.
IlliGAL technical report 2009001. You can download the pdf here. More information is also available at the Meandre website as part of the SEASR project.
Abstract: Data-intensive computing has positioned itself as a valuable programming paradigm to efficiently approach problems requiring processing very large volumes of data. This paper presents a pilot study about how to apply the data-intensive computing […]

by Llorà, X.

IlliGAL technical report 2009001. You can download the pdf here. More information is also available at the Meandre website as part of the SEASR project.

Abstract: Data-intensive computing has positioned itself as a valuable programming paradigm to efficiently approach problems requiring processing very large volumes of data. This paper presents a pilot study about how to apply the data-intensive computing paradigm to evolutionary computation algorithms. Two representative cases—selectorecombinative genetic algorithms and estimation of distribution algorithms—are presented, analyzed, discussed. This study shows that equivalent data-intensive computing evolutionary computation algorithms can be easily developed, providing robust and scalable algorithms for the multicore-computing era. Experimental results show how such algorithms scale with the number of available cores without further modification.