In this paper, we investigate the hypothesis that plan recognition can significantly improve the performance of a casebased reinforcement learner in an adversarial action selectio...
We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
Exploration/Exploitation equilibrium is one of the most challenging issues in reinforcement learning area as well as learning classifier systems such as XCS. In this paper1 , an i...
Agents that operate in a multi-agent system can benefit significantly from adapting to other agents while interacting with them. This work presents a general architecture for a ...
: Nowadays, advanced E-Learning systems are generally pedagogy-aware. Commonly, these systems include facilities for defining so-called learning scenarios that reflect sophisticate...