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...
The aim of this research is to develop an adaptive agent based model of auction scenarios commonly used in auction theory to help understand how competitors in auctions reach equil...
Transfer learning problems are typically framed as leveraging knowledge learned on a source task to improve learning on a related, but different, target task. Current transfer met...
E-blended learning as a new methodology will be explained. E-blended learning scenario for distance learners will include live sessions. During the last years we developed e-learn...
Learning the reward function of an agent by observing its behavior is termed inverse reinforcement learning and has applications in learning from demonstration or apprenticeship l...