Searching the space of policies directly for the optimal policy has been one popular method for solving partially observable reinforcement learning problems. Typically, with each ...
We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable orderi...
We study the problem of learning a kernel which minimizes a regularization error functional such as that used in regularization networks or support vector machines. We consider thi...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
In this paper, we propose a new integration approach to simulate an Autonomous Virtual Agent's cognitive learning of a task for interactive Virtual Environment applications. O...
This paper describes the Mediating Agent, an animated pedagogical agent inserted in a computational system for distance learning, which has the goal of motivating the student to le...