It is known that the complexity of the reinforcement learning algorithms, such as Q-learning, may be exponential in the number of environment’s states. It was shown, however, th...
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision fr...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
One of the key issues in designing appropriate and effective learning environments is understanding how learners advance and what factors contribute to their progress. This holds...
This article presents the description of the objectives, the structure and the functionality of an interactive system intended to focus the teaching on the performanceof the stude...
Nowadays, there is a growing need for providing novel solutions to facilitate active learning in dependency environments. This paper present a multiagent architecture that incorpor...