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The paper reviews current research results integrating machine learning and agent technologies. Although complementary solutions from both fields are discussed the focus is on using agent technology in the field of machine learning with a particular interest on applying agent-based solutions to supervised learning. The paper contains a short review of applications, in which machine learning methods have been used to support agent learning capabilities. This is followed by a corresponding review of machine learning methods and tools in which agent technology plays an important role. Final part gives a more detailed description of some example machine learning models and solutions where the asynchronous team of agents paradigm has been implemented to support the machine learning methods and which have been developed by the author and his research group.