The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Intelligent systems need to store their experience so that it can be reused. A memory for such systems needs to efficiently organize and search previous experience and to retriev...
Vicarious Learning is learning from watching others learn. We believe that this is a powerful model for computer-based learning. Learning episodes can be captured and replayed to ...
Understanding conceptual change is an important problem in modeling human cognition and in making integrated AI systems that can learn autonomously. This paper describes a model o...
We describe a framework that helps students learn from examples by generating example problem solutions whose level of detail is tailored to the students' domain knowledge. T...