Carnegie Mellon Robotics Institute
Cooperative and coordinated behavior that are observable in animal societies are very attractive and have been the motivation for my research for recent years.
I am investigating two key areas in the multi-agent domain. One is to throw light on the mechanism of generating cooperation. The other is to realize the cooperative behavior in practical systems by means of machine learning frameworks to integrate the top-down knowledge (symbolic and structured) and bottom-up knowledge (acquired through reinforcement learning and evolution).
I have proposed experience-based reinforcement learning algorithm which is very effective to emerge adaptive behaviors in the dynamic domain where includes multiple learning-entities. This algorithm works well even in un uncertain domain where agents can not have perfect information around the world.
Education and teaching are very important in making children, robots and other kind of creatures do the right thing.
|Research Interest Keywords|
|education, game theory, machine learning, planning|
|The Robotics Institute is part of the School of Computer Science, Carnegie Mellon University.|
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