The importance of mutation varies across evolutionary computation domains including: genetic programming, evolution strategies, and genetic algorithms. In the genetic programming ...
The population size in evolutionary computation is a significant parameter affecting computational effort and the ability to successfully evolve solutions. We find that population...
In this paper, we address the problem of finding gene regulatory networks from experimental DNA microarray data. We focus on the evaluation of the performance of different evoluti...
Christian Spieth, Rene Worzischek, Felix Streicher...
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
With the increasing emphasis on dependability in complex, distributed systems, it is essential that system development can be done gradually and at different levels of detail. In ...
Einar Broch Johnsen, Olaf Owe, Ellen Munthe-Kaas, ...