The paper presents the main findings of the ELeGI project, namely its learning model and software architecture to support the creation and execution of complex learning processes....
We consider the task of learning mappings from sequential data to real-valued responses. We present and evaluate an approach to learning a type of hidden Markov model (HMM) for re...
Argumentation is omnipresent in our lives and therefore an important skill to learn. While classic face-to-face argumentation and debate has advantages in helping people learn to a...
Frank Loll, Oliver Scheuer, Bruce M. McLaren, Niel...
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
Model based learning systems usually face to a problem of forgetting as a result of the incremental learning of new instances. Normally, the systems have to re-learn past instances...