Name
Abstract | ||
|---|---|---|
The evolution of an effective central model of action selection and behavioral modules have already been revised in previous papers. The central model has been set to resolve a foraging task, where specific modules for exploring the environment and for handling the collection and delivery of cylinders have been developed. Evolution has been used to adjust the selection parameters of the model and the neural weights of the exploring behaviors. However, in this paper the focus is on the use of genetic algorithms for coevolving both the selection parameters and the exploring behaviors. The main goal of this study is to reduce the number of decisions made by the human designer. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-73055-2_46 | IWINAC (2) |
Keywords | Field | DocType |
central action selection,effective central model,main goal,genetic algorithm,behavioral module,foraging task,central model,selection parameter,robot behavior,neural weight,human designer,action selection,genetic algorithms,coevolution | Coevolution,Computer science,Artificial intelligence,Behavior-based robotics,Action selection,Foraging,Genetic algorithm,Machine learning | Conference |
Volume | ISSN | Citations |
4528 | 0302-9743 | 1 |
PageRank | References | Authors |
0.36 | 7 | 1 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fernando Montes-Gonzalez | 1 | 12 | 3.89 |