Name
Abstract | ||
|---|---|---|
XCSF approximates function surfaces by evolving a suitable clustering of the input space, so that a simple -- typically linear -- predictor yields sufficient accuracy in each cluster. With an increasing number of distinct output dimensions, however, the accuracy of local predictions typically decreases. We analyze the performance of a single XCSF instance and compare it to the performance of a multiple-instance XCSF, where each instance predicts one dimension of the output. We show that dependent on the problem at hand, the multiple-instance XCSF approach is highly advantageous. In particular, we show that the more local linearity structures differ, the more a modularized approximation by multiple XCSF instances pays off. In fact, if modularization is not applied, the problem complexity may increase exponentially in the number of approximately orthogonally-structured output dimensions. To relate these results also to current XCSF application options, we show that the multiple-instance XCSF approach can also be applied to the problem of learning a compact model of the Jacobian of the forward-kinematics of a seven degree of freedom anthropomorphic robot arm for inverse robot arm control in simulation. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/2001576.2001744 | GECCO |
Keywords | Field | DocType |
multiple xcsf instance,freedom anthropomorphic robot arm,increasing number,multiple-instance xcsf approach,orthogonally-structured output dimension,multiple output dimension,problem complexity,current xcsf application option,distinct output dimension,single xcsf instance,multiple-instance xcsf,robotics,degree of freedom,learning classifier system,robot arm,function approximation,modularization | Inverse,Degrees of freedom (statistics),Robotic arm,Mathematical optimization,Function approximation,Jacobian matrix and determinant,Computer science,Linearity,Artificial intelligence,Cluster analysis,Robotics,Machine learning | Conference |
Citations | PageRank | References |
4 | 0.40 | 14 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martin V. Butz | 1 | 1065 | 85.21 |
| Patrick O. Stalph | 2 | 74 | 5.95 |