GEM 2014 - The 2014 International Conference on Genetic and Evolutionary Methods (GEM'14)

You are invited to submit a paper for consideration. All accepted papers will be published in printed conference books/proceedings (ISBN) and will also be made available online. The proceedings will be indexed in science citation databases that track citation frequency/data for each paper. In addition, like prior years, extended versions of selected papers (about 35%) will appear in journals and edited research books (publishers include: Springer, Elsevier, BMC, and others). See the following links for a small subset of the publications based on the Congress: (some of these books and special issues have already received the top 25% downloads in their respective fields - we also have a number of Elsevier and Springer books in the pipeline based on the last offering of the congress):
http://store.elsevier.com/Emerging-Trends-in-ICT-S...
http://www.biomedcentral.com/bmcmedgenomics/supple...
http://www.springer.com/life+sciences/bioinformati...
http://www.springer.com/life+sciences/bioinformati...
http://www.biomedcentral.com/1471-2164/9/S1/I1
http://www.springer.com/series/11769
http://www.biomedcentral.com/1752-0509/5?issue=S3
http://pubmedcentralcanada.ca/pmcc/articles/PMC328...
http://pubmedcentralcanada.ca/pmcc/articles/PMC270...
http://pubmedcentralcanada.ca/pmcc/articles/PMC299...
GEM'14 is composed of a number of tracks, including: tutorials, sessions, workshops, posters, and panel discussions. The conference will be held July 21-24, 2014, Las Vegas, USA.
Topics of interest include, but are not limited to, the following:
Machine learning
Genetic algorithms
Artificial life
Genetic benchmarks and software packages
Optimization methodologies
Swarm intelligence and optimization
Artificial immune systems
Evolutionary programming
Bioinformatics, computational biology, systems & synthetic biology
Adaptive behavior-based systems
Fuzzy systems and evolutionary computing
Biologically inspired systems
Evolutionary strategies
Genetic programming
Combinatorial optimization problems
Ant colony optimization
Learning methods
Agent technologies
Parallel/distributed evolutionary algorithms
Hybrid genetic / memetic algorithms
Evolvable hardware
Evolutionary scheduling
Search based strategies
Hyper heuristics
Evolutionary multi-objective optimization
Prediction methods
Co-evolution
Novel methodologies
Robotics
Applications