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DNVA: A Tool for Visualizing and Analyzing Multi-agent Learning in Networks
2014
2014 IEEE 26th International Conference on Tools with Artificial Intelligence
Networks are seen everywhere in our modern life, including the Internet, the Grid, P2P file sharing, and sensor networks. Consequently, researchers in Artificial Intelligence (and Multi-Agent Systems in particular) have been actively seeking methods for optimizing the performance of these networks. A promising yet challenging optimization direction is multi-agent learning: allowing agents to adapt their behavior through interaction with one another. However, understanding the dynamics of an
doi:10.1109/ictai.2014.67
dblp:conf/ictai/AbdallahSRSL14
fatcat:wz4zdv6kxzd7vkppbmsfij4xzm