The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
My research attempts to address on-line action selection in reinforcement learning from a Bayesian perspective. The idea is to develop more effective action selection techniques b...
An important issue in reinforcement learning is how to incorporate expert knowledge in a principled manner, especially as we scale up to real-world tasks. In this paper, we presen...
Eric Wiewiora, Garrison W. Cottrell, Charles Elkan
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
cal networks in the learning of abstract and effector-specific representations of motor sequences. Neuroimage. 32, 714-727. (Neuroimage Editor’s Choice Award, 2006) Daw, N. D. Do...