- author = "David Medernach",
- title = "Comparative study of effects of fitness landscape changes in open-ended evolutionary simulations and in Genetic Programming",
- school = "Department of Computer Science \& Information Systems, Faculty of Science and Engineering, University of Limerick",
- year = "2017",
- address = "Ireland",
- keywords = "genetic algorithms, genetic programming",
-
URL = "
https://ulir.ul.ie/bitstream/handle/10344/6103/Medernach_2017_comparative.pdf",
-
URL = "
http://hdl.handle.net/10344/6103",
- size = "265 pages",
-
abstract = "The biological world where natural selection takes
place is a world constantly affected by external
physical phenomena, whether cyclical and regular, such
as the rotation of the earth, or punctual such as when
a meteorite strikes the earth. It is recognized that
these phenomena affect the evolution of life, but their
interaction with natural selection have not yet been
fully explored.
This thesis studies the effects of environmental fluctuations via evolutionary simulations. In particular, we propose to study them through simulations of Genetic Programming as well as Artificial Life evolving virtual ecosystems.
We first present the history of natural selection as well as artificial life and genetic programming, focusing on the role of environmental fluctuations in these three fields of research.
We then examine the effects of such fluctuations on virtual ecosystems. We create a new virtual ecosystem which we call HetCA, that is based on cellular automata with heterogeneous transition rules. In this simulation, we test effects of these fluctuations on the evolutionary progress as well as on the level of selection and show that the type of fluctuation determine the level of selection.
Finally, we study the effects of such fluctuations in Genetic Programming, firstly through an extension of Random Interleaved Sampling and then by creating a new method of Genetic Programming which we call Wave. We note that, on the studied problems, Wave is a very competitive method compared to a selection of benchmarks including non-evolutionary computation based optimization methods.",
- notes = "Supervisor: Prof. Conor Ryan",
