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ATAL
2007
Springer
14 years 3 months ago
Reducing the complexity of multiagent reinforcement learning
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...
Andriy Burkov, Brahim Chaib-draa
ATAL
2008
Springer
13 years 11 months ago
Efficient multi-agent reinforcement learning through automated supervision
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
ATAL
2005
Springer
14 years 2 months ago
Multiagent simulation of learning environments
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...
Elizabeth Sklar, Mathew Davies
FLAIRS
2000
13 years 10 months ago
A Multiagent Architecture to Support Distance Learning Personalization on the Web
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...
Jesus Boticario, Elena Gaudioso
IDEAL
2009
Springer
14 years 3 months ago
Improving the Language Active Learning with Multiagent Systems
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...
Cristian Pinzón, Vivian López, Javie...