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Agent mining
From Wikipedia, the free encyclopedia
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Agent mining is a research field that combines two areas of computer science: multiagent systems and data mining. It explores how intelligent computer agents can work together to discover, analyze, and learn from large amounts of data more effectively than traditional methods.[1][2]
 | A major contributor to this article appears to have a close connection with its subject. (April 2016) |
Historical context
The interaction and the integration between multiagent systems and data mining have a long history.[3][4] The very early work on agent mining focused on agent-based knowledge discovery,[5] agent-based distributed data mining,[6][7] and agent-based distributed machine learning,[8] and using data mining to enhance agent intelligence.[9]
The International Workshop on Agents and Data Mining Interaction[10] has been held for more than 10 times, co-located with the International Conference on Autonomous Agents and Multi-Agent Systems. Several proceedings are available from Springer Lecture Notes in Computer Science.
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References
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