In this paper, a new hybrid adaptation model for cancer diagnosis has been developed. It combines transformational and hierarchical adaptation techniques with artificial neural ne...
Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
Learning processes allow the central nervous system to learn relationships between stimuli. Even stimuli from different modalities can easily be associated, and these associations ...
Matthew Cook, Florian Jug, Christoph Krautz, Angel...
We present an algorithm, HI-MAT (Hierarchy Induction via Models And Trajectories), that discovers MAXQ task hierarchies by applying dynamic Bayesian network models to a successful...
We present an architectural approach to learning problem solving skills from demonstration, using internal models to represent problem-solving operational knowledge. Internal forwa...
Haris Dindo, Antonio Chella, Giuseppe La Tona, Mon...