A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
The class of stochastic nonlinear programming (SNLP) problems is important in optimization due to the presence of nonlinearity and uncertainty in many applications, including thos...
—The problem of automatically generating hardware modules from a high level representation of an application has been at the research forefront in the last few years. In this pap...
Multi-stage programming (MSP) provides a disciplined approach to run-time code generation. In the purely functional setting, it has been shown how MSP can be used to reduce the ov...
Edwin Westbrook, Mathias Ricken, Jun Inoue, Yilong...
We consider the task of learning to accurately follow a trajectory in a vehicle such as a car or helicopter. A number of dynamic programming algorithms such as Differential Dynami...
J. Zico Kolter, Adam Coates, Andrew Y. Ng, Yi Gu, ...