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Skip to Search Results- 3Policy Gradient
- 3Reinforcement Learning
- 1Baseline
- 1Decision Trees
- 1Real-Time Learning
- 1Representation Learning
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Spring 2015
Much of the focus on finding good representations in reinforcement learning has been on learning complex non-linear predictors of value. Methods like policy gradient, that do not learn a value function and instead directly represent policy, often need fewer parameters to learn good policies....
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Fall 2021
Continuous-time reinforcement learning tasks commonly use discrete time steps of fixed cycle times for actions. Choosing a small action-cycle time in such tasks allows reinforcement learning agents fast reaction and a more temporally detailed perception of the environment. The learning...
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Spring 2015
This thesis consists of two independent projects, each contributing to a central goal of artificial intelligence research: to build computer systems that are capable of performing tasks and solving problems without problem-specific direction from us, their designers. I focus on two formal...