Multilayered feedforward neural networks possess a number of properties which make them particularly suited to complex pattern classification problems. However, their application ...
Probabilistic Roadmaps (PRM) are a commonly used class of algorithms for robot navigation tasks where obstacles are present in the environment. We examine the situation where the ...
Abstract. Deep Neural Networks (DNN) propose a new and efficient ML architecture based on the layer-wise building of several representation layers. A critical issue for DNNs remain...
We introduce potential fitness, a variant of fitness function that operates in the space of schemata and is applicable to tree-based genetic programing. The proposed evaluation ...
Probabilistic model building methods can render difficult problems feasible by identifying and exploiting dependencies. They build a probabilistic model from the statistical prope...