Name
Title | ||
|---|---|---|
Co-evolving an effective fitness sample: experiments in symbolic regression and distributed robot control |
Abstract | ||
|---|---|---|
We investigate two techniques for co-evolving and sampling from a population of fitness cases, and compare these with a random sampling technique. We design three symbolic regression problems on which to test these techniques, and also measure their relative performance on a modular robot control problem. The methods have varying relative performance, but in all of our experiments, at least one of the co-evolutionary methods outperforms the random sampling method by guiding evolution, with substantially fewer fitness evaluations, toward solutions that generalize best on an out-of-sample test set. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1145/508791.508899 | SAC |
Keywords | Field | DocType |
random sampling method,guiding evolution,out-of-sample test set,relative performance,fitness case,co-evolutionary method,effective fitness sample,modular robot control problem,random sampling technique,fewer fitness evaluation,symbolic regression problem,genetic algorithms,robot control,co evolution,genetic programming,random sampling,genetic algorithm | Effective fitness,Population,Robot control,Computer science,Fitness proportionate selection,Fitness approximation,Artificial intelligence,Sampling (statistics),Symbolic regression,Machine learning,Test set | Conference |
ISBN | Citations | PageRank |
1-58113-445-2 | 7 | 0.58 |
References | Authors | |
12 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Brad Dolin | 1 | 36 | 5.56 |
| Forrest H. Bennett, III | 2 | 157 | 24.76 |
| Eleanor Rieffel | 3 | 488 | 48.71 |