Call for Papers
Special Session on Speciation
IEEE Congress on Evolutionary Computation (IEEE CEC 2019)
Wellington, New Zealand
10-13 June 2019
submission deadline: 7 January 2019
http://cs.conncoll.edu/parker/Speciation
Although Evolutionary Algorithms are very good at mimicking adaptation within a species to optimize solutions for difficult problems, creating algorithms that can mimic the development of two or more species from a common ancestor has been a challenge.
There are versions of Evolutionary Algorithms that have some characteristics of speciation, but none that match natural processes. Such algorithms would be a good step in the development of a general purpose Evolutionary Algorithm and would help in
understanding the principles of evolution. In regards to this research, we consider a population to be distinct (and a separate species) if it is made up of individuals that are unable to produce viable offspring with individuals from the other
population or if offspring are produced, they are sterile. The short term goal, which is reasonable for this special session, is to have individuals of differing species choose not to mate and if they do produce offspring, the offspring do not continue
to reproduce. In this way, the gene pools for each of the species will be isolated.
The purpose of this special session is to bring together people working on Evolutionary Algorithms that tend toward or have the potential for speciation. Some possible topics of interest include:
- Evolutionary algorithms mimicking allopatric or sympatric speciation
- Environments for research in natural speciation
- Biologically-inspired models of interactive agents
- Spatially-structured populations
- Niching
- Island models
- Use of topology in populations
- Formation of sub-populations
- Selection criteria in evolutionary algorithms
- Co-evolution
- Multi-agent systems
- Multimodal function optimization
Organizers
Gary Parker
Department of Computer Science, Connecticut College, New London, Connecticut, USA
parker@conncoll.edu
Peter Whigham
Department of Information Science, University of Otago, Dunedin, Otago, New Zealand.
peter.whigham@otago.ac.nz
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