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GECCO
2006
Springer
218views Optimization» more  GECCO 2006»
15 years 10 months ago
A survey of mutation techniques in genetic programming
The importance of mutation varies across evolutionary computation domains including: genetic programming, evolution strategies, and genetic algorithms. In the genetic programming ...
Alan Piszcz, Terence Soule
GECCO
2006
Springer
139views Optimization» more  GECCO 2006»
15 years 10 months ago
Genetic programming: optimal population sizes for varying complexity problems
The population size in evolutionary computation is a significant parameter affecting computational effort and the ability to successfully evolve solutions. We find that population...
Alan Piszcz, Terence Soule
GECCO
2006
Springer
220views Optimization» more  GECCO 2006»
15 years 10 months ago
Comparing evolutionary algorithms on the problem of network inference
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...
GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
15 years 10 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
APAQS
2001
IEEE
15 years 10 months ago
Incremental Fault-Tolerant Design in an Object-Oriented Setting
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, ...