Abstract. This paper has as main goal to develop a hybrid expert system to minimize some of the complexity problems related to arti cial intelligence eld. For instance, we can ment...
Lourdes Mattos Brasil, Fernando Mendes de Azevedo,...
Deep-layer machine learning architectures continue to emerge as a promising biologically-inspired framework for achieving scalable perception in artificial agents. State inference ...
This paper presents an integrated modeling framework where the learning and knowledge retrieval mechanisms of the ACT-R cognitive architecture are combined with a semantic resource...
In order to implement real-time adaptive augmented cognition, one of the focal points of our present research involves understanding the dimensions of task complexity. Task comple...
Planning a path to a destination, given a number of options and obstacles, is a common task. We suggest a two-component cognitive model that combines retrieval of knowledge about t...