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My research interests center on learning in machines and animals. I have been working on developing learning algorithms that are useful for engineering applications but that also make contact with learning as studied by psychologists and neuroscientists. Although I make no claims to being either a psychologist or a neuroscientist, I spend a lot of my time interacting with psychologists and neuroscientists and reading literature in those fields. I feel strongly that new developments should be integrated as closely as possible with the state-of-the art in as many of the relevant fields as possible. It is also essential to understand how new developments relate to what others have done in the past.
In the case of reinforcement learning---whose main ideas go back a very long way---it has been immensely gratifying to participate in establishing new links between reinforcement learning and methods from the theory of stochastic optimal control. Especially exciting to me are the connections between temporal difference (TD) algorithms and the brain's dopamine system. These are partly responsible for rekindling my interest in reinforcement learning as an approach to building and understanding autonomous agents, rather than as a collection of methods for approximating solutions to large-scale engineering problems.
研究兴趣
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Autonomous Mental Development, IEEE Transactionsno. 2 (2010): 70-82
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