This paper briefly describes how ontologies can be used to model, validate and execute IMS Learning Design. The main contribution relies on incorporate the implicit knowledge foun...
The design and implementation of distributed real-time dependable systems is often dominated by non-functional considerations like timeliness, object placement and fault tolerance...
This paper argues that multiagent learning is a potential “killer application” for generative and developmental systems (GDS) because key challenges in learning to coordinate ...
Biological brains can adapt and learn from past experience. In neuroevolution, i.e. evolving artificial neural networks (ANNs), one way that agents controlled by ANNs can evolve t...
We address in this paper the question of how the knowledge of the marginal distribution P(x) can be incorporated in a learning algorithm. We suggest three theoretical methods for ...