Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
In this article, a real-coded genetic algorithm (GA) is proposed capable of simultaneously optimizing the structure of a system (number of inputs, membership functions and rules) ...
An on-road analytical tire model has been developed to predict tire forces and moments at the tire/road interface. The model is computationally efficient and it only requires a li...
The Semantic Web consists of many billions of statements made of terms that are either URIs or literals. Since these terms usually consist of long sequences of characters, an effe...
Generative representations allow the reuse of code and thus facilitate the evolution of repeated phenotypic themes or modules. It has been shown that generative representations pe...